Allergic diseases are highly prevalent disorders, mainly in industrialized countries where they constitute a high global health problem. Allergy is defined as an immune response “shifted toward a type 2 inflammation” induced by the interaction between the antigen (allergen) and IgE antibodies bound to mast cells and basophils that induce the release of inflammatory mediators that cause the clinical symptoms. Currently, allergen-specific immunotherapy (AIT) is the only treatment able to change the course of these diseases, modifying the type 2 inflammatory response by an allergenic tolerance, where the implication of T regulatory (Treg) cells is considered essential. The pollen of the olive tree is one of the most prevalent causes of respiratory allergic diseases in Mediterranean countries, inducing mainly nasal and conjunctival symptoms, although, in areas with a high antigenic load, olive-tree pollen may cause asthma exacerbation. Classically, olive-pollen allergy treatment has been based on specific immunotherapy using whole-olive pollen extracts. Despite extracts standardization, the effectiveness of this strategy varies widely, therefore there is a need for more effective AIT approaches. One of the most attractive is the use of synthetic peptides representing the B- or T-cell epitopes of the main allergens. This review summarizes experimental evidence of several T-cell epitopes derived from the Ole e 1 sequence to modulate the response to olive pollen in vitro, associated with several possible mechanisms that these peptides could be inducing, showing their usefulness as a safe preventive tool for these complex diseases.

Background: Macrophage scavenger receptor 1 (MSR1) has mostly been described in macrophages, but we previously found a significant gene expression increase in peripheral blood mononuclear cells (PBMCs) of asthmatic patients. Objective: To confirm those results and to define its cellular origin in PBMCs. Methods: Four groups of subjects were studied: healthy controls (C), nonallergic asthmatic (NA), allergic asthmatic (AA), and chronic obstructive pulmonary disease (COPD) patients. RNA was extracted from PBMCs. MSR1 gene expression was analyzed by RT-qPCR. The presence of MSR1 on the cellular surface of PBMC cellular subtypes was analyzed by confocal microscopy and flow cytometry. Results: MSR1 gene expression was significantly increased in the three clinical conditions compared to the healthy control group, with substantial variations according to disease type and severity. MSR1 expression on T cells (CD4+ and CD8+), B cells, and monocytes was confirmed by confocal microscopy and flow cytometry. In all clinical groups, the four immune cell subtypes studied expressed MSR1, with a greater expression on B lymphocytes and monocytes, exhibiting differences according to disease and severity. Conclusions: This is the first description of MSR1’s presence on lymphocytes’ surfaces and reinforces the potential role of MSR1 as a player in asthma and COPD.

Highly prevalent respiratory diseases such as asthma and allergy remain a pressing health challenge. Currently, there is an unmet need for precise diagnostic tools capable of predicting the great heterogeneity of these illnesses. In a previous study of 94 asthma/respiratory allergy biomarker candidates, we defined a group of potential biomarkers to distinguish clinical phenotypes (i.e. nonallergic asthma, allergic asthma, respiratory allergy without asthma) and disease severity. Here, we analyze our experimental results using complex algorithmic approaches that establish holistic disease models (systems biology), combining these insights with information available in specialized databases developed worldwide. With this approach, we aim to prioritize the most relevant biomarkers according to their specificity and mechanistic implication with molecular motifs of the diseases. The Therapeutic Performance Mapping System (Anaxomics’ TPMS technology) was used to generate one mathematical model per disease: allergic asthma (AA), non-allergic asthma (NA), and respiratory allergy (RA), defining specific molecular motifs for each. The relationship of our molecular biomarker candidates and each disease was analyzed by artificial neural networks (ANNs) scores. These analyses prioritized molecular biomarkers specific to the diseases and to particular molecular motifs. As a first step, molecular characterization of the pathophysiological processes of AA defined 16 molecular motifs: 2 specific for AA, 2 shared with RA, and 12 shared with NA. Mechanistic analysis showed 17 proteins that were strongly related to AA. Eleven proteins were associated with RA and 16 proteins with NA. Specificity analysis showed that 12 proteins were specific to AA, 7 were specific to RA, and 2 to NA. Finally, a triggering analysis revealed a relevant role for AKT1, STAT1, and MAPK13 in all three conditions and for TLR4 in asthmatic diseases (AA and NA). In conclusion, this study has enabled us to prioritize biomarkers depending on the functionality associated with each disease and with specific molecular motifs, which could improve the definition and usefulness of new molecular biomarkers.