Plasma Galectin-3 and urine proteomics predict FEV1 improvement in omalizumab-treated patients with severe allergic asthma: Results from the PROXIMA sub-study

The Role of Galectins in Asthma Pathophysiology: A Comprehensive Review

Galectins are a group of β-galactoside-binding proteins with several roles in immune response, cellular adhesion, and inflammation development. Current evidence suggest that these proteins could play a crucial role in many respiratory diseases such as pulmonary fibrosis, lung cancer, and respiratory infections. From this standpoint, an increasing body of evidence have recognized galectins as potential biomarkers involved in several aspects of asthma pathophysiology. Among them, galectin-3 (Gal-3), galectin-9 (Gal-9), and galectin-10 (Gal-10) are the most extensively studied in human and animal asthma models. These galectins can affect T helper 2 (Th2) and non-Th2 inflammation, mucus production, airway responsiveness, and bronchial remodeling. Nevertheless, while higher Gal-3 and Gal-9 concentrations are associated with a stronger degree of Th-2 phlogosis, Gal-10, which forms Charcot-Leyden Crystals (CLCs), correlates with sputum eosinophilic count, interleukin-5 (IL-5) production, and immunoglobulin E (IgE) secretion. Finally, several galectins have shown potential in clinical response monitoring after inhaled corticosteroids (ICS) and biologic therapies, confirming their potential role as reliable biomarkers in patients with asthma.

Eosinophilic Asthma: Pathophysiology and Therapeutic Horizons

Asthma is a prevalent chronic non-communicable disease, affecting approximately 300 million people worldwide. It is characterized by significant airway inflammation, hyperresponsiveness, obstruction, and remodeling. Eosinophilic asthma, a subtype of asthma, involves the accumulation of eosinophils in the airways. These eosinophils release mediators and cytokines, contributing to severe airway inflammation and tissue damage. Emerging evidence suggests that targeting eosinophils could reduce airway remodeling and slow the progression of asthma. To achieve this, it is essential to understand the immunopathology of asthma, identify specific eosinophil-associated biomarkers, and categorize patients more accurately based on the clinical characteristics (phenotypes) and underlying pathobiological mechanisms (endotypes). This review delves into the role of eosinophils in exacerbating severe asthma, exploring various phenotypes and endotypes, as well as biomarkers. It also examines the current and emerging biological agents that target eosinophils in eosinophilic asthma. By focusing on these aspects, both researchers and clinicians can advance the development of targeted therapies to combat eosinophilic pathology in severe asthma.

A robust mRNA signature obtained via recursive ensemble feature selection predicts the responsiveness of omalizumab in moderate-to-severe asthma

BACKGROUND

Not being well controlled by therapy with inhaled corticosteroids and long-acting β2 agonist bronchodilators is a major concern for severe-asthma patients. The current treatment option for these patients is the use of biologicals such as anti-IgE treatment, omalizumab, as an add-on therapy. Despite the accepted use of omalizumab, patients do not always benefit from it. Therefore, there is a need to identify reliable biomarkers as predictors of omalizumab response.

METHODS

Two novel computational algorithms, machine-learning based Recursive Ensemble Feature Selection (REFS) and rule-based algorithm Logic Explainable Networks (LEN), were used on open accessible mRNA expression data from moderate-to-severe asthma patients to identify genes as predictors of omalizumab response.

RESULTS

With REFS, the number of features was reduced from 28,402 genes to 5 genes while obtaining a cross-validated accuracy of 0.975. The 5 responsiveness predictive genes encode the following proteins: Coiled-coil domain- containing protein 113 (CCDC113), Solute Carrier Family 26 Member 8 (SLC26A), Protein Phosphatase 1 Regulatory Subunit 3D (PPP1R3D), C-Type lectin Domain Family 4 member C (CLEC4C) and LOC100131780 (not annotated). The LEN algorithm found 4 identical genes with REFS: CCDC113, SLC26A8 PPP1R3D and LOC100131780. Literature research showed that the 4 identified responsiveness predicting genes are associated with mucosal immunity, cell metabolism, and airway remodeling.

CONCLUSION AND CLINICAL RELEVANCE

Both computational methods show 4 identical genes as predictors of omalizumab response in moderate-to-severe asthma patients. The obtained high accuracy indicates that our approach has potential in clinical settings. Future studies in relevant cohort data should validate our computational approach.

Real-world super-response to biologics in severe asthma: A French monocentric retrospective cohort study

BACKGROUND

Biologics have dramatically improved outcomes in severe T2-high asthma. Although the identification of patients with the best response is key to understand the efficacy of these agents and select the best target populations, the definition and predictors of super-response are not fully established yet.

METHODS

This study aimed to describe super-response and to identify predictors of super-response to biologics in a French severe eosinophilic asthma cohort followed in a severe asthma tertiary care center between January 2005 and December 2020. Super-response was defined a priori as no oral corticosteroids intake and no exacerbations over 12 months. Collected data at baseline and after 12 months included asthma history, comorbidities, clinical characteristics, lung function, T2-biomarkers, baseline asthma-related treatments, and asthma control.

RESULTS

Among 157 patients assessed for eligibility, 108 were included, corresponding to 166 treatments with biologics. Overall response rate was 63.2 % (105/166) and super-response rate was 39.7 % (66/166). In omalizumab group (n = 67), lower dose of oral corticosteroids in maintenance was the only factor associated with super-response (p = 0.008). In the anti-IL-5/anti-IL-5R group (n = 99), absence or lower dose of oral corticosteroids in maintenance and absence of eosinophilic granulomatosis with polyangiitis were statistically associated with super-response (p = 0.009, p = 0.001 and p = 0.02 respectively).

CONCLUSION

In this real-life study in severe T2-high asthma patients, a lower dose or absence of daily oral corticosteroids and absence of eosinophilic granulomatosis with polyangiitis were the only identifiable predictors of super-response to biologics. Physicians should not wait for maintenance oral corticosteroids to be required before considering the initiation of a biologic in severe asthma.

Serum biomarkers of remodeling in severe asthma with fixed airway obstruction and the potential role of KL-6

Over 3% of asthmatic patients are affected by a particularly severe form of the disease ("severe asthma", SA) which is often refractory to standard treatment. Airway remodeling (AR), which can be considered a critical characteristic of approximately half of all patients with SA and currently thought to be the main mechanism triggering fixed airway obstruction (FAO), seems to be a key factor affecting a patient's outcome. Despite the collective efforts of internationally renowned experts, to date only a few biomarkers indicative of AR and no recognizable biomarkers of lung parenchymal remodeling have been identified. This work examines the pathogenesis of airway and lung parenchymal remodeling and the serum biomarkers that may be able to identify the severe asthmatic patients who may develop FAO. The study also aims to examine if Krebs von den Lungen-6 (KL-6) could be considered a diagnostic biomarker of lung structural damage in SA.

Inhibition of LPS-Induced Inflammatory Response of Oral Mesenchymal Stem Cells in the Presence of Galectin-3

Galectin-3 (GAL-3) is a beta-galactoside binding lectin produced by mesenchymal stem cells (MSCs) and other cell sources under inflammatory conditions. Several studies have reported that GAL-3 exerts an anti-inflammatory action, regulated by its natural ligand GAL-3 BP. In the present study, we aimed to assess the GAL-3 mediated regulation of the MSC function in an LPS-induced inflammation setting. Human gingival mesenchymal stem cells (hGMSCs) were stimulated in vitro with LPSs; the expression of TLR4, NFκB p65, MyD88 and NALP3 were assessed in the hGMSCs via immunofluorescence imaging using confocal microscopy, Western blot assay, and RT-PCR before and after the addition of GAL-3, both alone and with the addition of its inhibitors. LPSs stimulated the expression of TLR4, NFκB p65, MyD88 and NALP3 in hGMSCs, which was inhibited by GAL-3. The addition of either GAL3-BP or the antibody to GAL-3 were able to revert the GAL-3-mediated effects, restoring the expression of TLR4, NFκB p65, MyD88 and NALP3. GAL-3 induces the downregulation of the LPS-induced inflammatory program in MSCs.

Phenotypes and Endotypes in Asthma

Asthma is a broadly encompassing diagnosis of airway inflammation with significant variability in presentation and response. Advances in molecular techniques and imaging have unraveled the delicate mechanistic tapestry responsible for the underlying inflammatory pathways in asthma. The elucidation of biomarkers and cellular components specific to these inflammatory pathways allowed for the categorization of asthma from generic phenotypes to more specific mechanistic endotypes, with two prominent subgroups emerging based on the level of Type 2 inflammation present - T2 high and T2 low (or non-T2). Sophisticated modeling and cluster analyses using a combination of clinical, physiologic, and biomarker parameters have permitted the identification of subendotypes within the broader T2 umbrella. This mechanistic-driven classification schema for asthma has dramatically altered the landscape of asthma management with the discovery and approval of targeted biologic therapies and has ushered in a new era of personalized precision medicine in asthma.

Role of clinical biomarkers in predicting the effectiveness of omalizumab

OBJECTIVE

To explore whether baseline clinical biomarkers and characteristics can be used to predict the responsiveness of omalizumab.

METHODS

We retrospectively analyzed a cohort of patients with severe asthma who received omalizumab treatment and collected their baseline data and relevant laboratory examination results along with case records of omalizumab treatment responsiveness after 16 weeks. We compared the differences in variables between the group of patients that responded to omalizumab therapy and the non-responder group, and then performed univariate and multivariate logistic regression. Finally, we analyzed the difference in response rate for subgroups by selecting cut-off values for the variables using Fisher's exact probability method.

RESULTS

This retrospective, single-center observational study enrolled 32 patients with severe asthma who were prescribed daily high-dose inhaled corticosteroids and long-acting β2 receptor agonists on long-acting muscarinic receptor antagonists with or without OCS. Data on age, sex, BMI, bronchial thermoplasty, FeNO, serum total IgE, FEV1, blood eosinophils, induced sputum eosinophils, blood basophils, and complications were not significantly different between the responder and non-responder groups. In the univariate and multivariate logistic regression, all the variants were not significant, and we were unable to build a regression model. We used normal high values and the mean or median of variables as cut-off values to create patient subgroups for the variables and found no significant difference in the omalizumab response rate between the subgroups.

CONCLUSION

The responsiveness of omalizumab is not associated with pretreatment clinical biomarkers, and these biomarkers should not be used to predict the responsiveness of omalizumab.

Precision Medicine in Asthma Therapy

Asthma is a complex, heterogeneous disease that necessitates a proper patient evaluation to decide the correct treatment and optimize disease control. The recent introduction of new target therapies for the most severe form of the disease has heralded a new era of treatment options, intending to treat and control specific molecular pathways in asthma pathophysiology. Precision medicine, using omics sciences, investigates biological and molecular mechanisms to find novel biomarkers that can be used to guide treatment selection and predict response. The identification of reliable biomarkers indicative of the pathological mechanisms in asthma is essential to unravel new potential treatment targets. In this chapter, we provide a general description of the currently available -omics techniques, focusing on their implications in asthma therapy.

miR-3934 regulates the apoptosis and secretion of inflammatory cytokines of basophils via targeting RAGE in asthma

Background

Several miRNAs are now known to have clear connections to the pathogenesis of asthma. The present study focused on the potential role of miR-3934 during asthma development.

Methods

miR-3934 was detected as a down-regulated miRNA in basophils by sequencing analysis. Next, the expression levels of miR-3934 in peripheral blood mononuclear cells of 50 asthma patients and 50 healthy volunteers were examined by RT-qPCR methods. The basophils were then treated with AGEs and transfected with miR-3934 mimics. The apoptosis levels were examined by flow cytometry assay; and the expression levels of cytokines were detected using the ELISA kits. Finally, the Western blot was performed to examined the expression of key molecules in the TGF-β/Smad signaling pathway.

Results

miR-3934 was down-regulated in the basophils of asthmatic patients. The expression of the pro-inflammatory cytokines IL-6, IL-8 and IL-33 was enhanced in basophils from asthmatic patients, and this effect was partially reversed by transfection of miR-3934 mimics. Furthermore, receiver operating characteristics analysis showed that miR-3934 levels can be used to distinguish asthma patients from healthy individuals. miR-3934 partially inhibited advanced glycation end products-induced increases in basophil apoptosis by suppressing expression of RAGE.

Conclusion

Our results indicate that miR-3934 acts to mitigate the pathogenesis of asthma by targeting RAGE and suppressing TGF-β/Smad signaling.

Allergic and eosinophilic asthma in the era of biomarkers and biologics: similarities, differences and misconceptions

OBJECTIVE

Severe asthma is associated with substantial personal and economic burden; maintaining disease control is the key management goal. Increased understanding of asthma heterogeneity and development of type 2 (T2)-targeting biologics has substantially advanced disease management and outcomes; however, despite both being driven by T2 inflammation, allergic and eosinophilic asthma have different treatment recommendations. We sought to better understand the similarities and differences between allergic and eosinophilic asthma and highlight where misconceptions may arise.

DATA SOURCES

Published articles, pivotal trials, post hoc analyses, and asthma clinical guidelines sourced from PubMed.

STUDY SELECTIONS

Sources reporting allergic and eosinophilic asthma classifications, disease mechanisms, and biomarkers associated with treatment response.

RESULTS

This review highlights that severe allergic and eosinophilic asthma are both driven by T2 inflammation with eosinophils playing a cardinal role. Despite this overlap, treatment recommendations differ based on asthma classification. T2 cytokine gene expression is a reasonably well-established research tool, but not a well-established biomarker in clinical practice, unlike blood eosinophil counts, fractional exhaled nitric oxide, and immunoglobulin E; the clinical relevance of immunoglobulin E as a predictive biomarker remains unclear.

CONCLUSION

Asthma classifications that can be easily characterized at patient level to ensure accurate diagnosis, predict disease trajectory, and treatment response are required. The current dichotomy of allergic and eosinophilic asthma classifications is likely too simplistic, given the similar eosinophil-mediated disease pathophysiology in both classifications. Our results provide future directions to guide clinically meaningful interpretation of asthma endophenotypes, which may improve understanding of severe asthma characterization and aid future advances in defining responders more precisely with personalized medicine approaches.

Shotgun Proteomics of Isolated Urinary Extracellular Vesicles for Investigating Respiratory Impedance in Healthy Preschoolers

Urine proteomic applications in children suggested their potential in discriminating between healthy subjects from those with respiratory diseases. The aim of the current study was to combine protein fractionation, by urinary extracellular vesicle isolation, and proteomics analysis in order to establish whether different patterns of respiratory impedance in healthy preschoolers can be characterized from a protein fingerprint. Twenty-one 3-5-yr-old healthy children, representative of 66 recruited subjects, were selected: 12 late preterm (LP) and 9 full-term (T) born. Children underwent measurement of respiratory impedance through Forced Oscillation Technique (FOT) and no significant differences between LP and T were found. Unbiased clustering, based on proteomic signatures, stratified three groups of children (A, B, C) with significantly different patterns of respiratory impedance, which was slightly worse in group A than in groups B and C. Six proteins (Tripeptidyl peptidase I (TPP1), Cubilin (CUBN), SerpinA4, SerpinF1, Thy-1 membrane glycoprotein (THY1) and Angiopoietin-related protein 2 (ANGPTL2)) were identified in order to type the membership of subjects to the three groups. The differential levels of the six proteins in groups A, B and C suggest that proteomic-based profiles of urinary fractionated exosomes could represent a link between respiratory impedance and underlying biological profiles in healthy preschool children.

CD3E as a new predictive biomarker of response to omalizumab treatment in asthma patients: Evidence from bioinformatic analysis

BACKGROUND AND OBJECTIVE

Omalizumab is a bio-targeted agent approved as add-on therapy for the treatment of severe asthma. Most patients with severe asthma show no response to omalizumab. American Thoracic Society (ATS) and European Respiratory Society (ERS) recommend blood eosinophil count and fractional exhaled nitric oxide (FeNO) as biomarkers with high value for increased response to omalizumab and periostin as a biomarker with a low value. In this study, we aimed to identify the biomarkers for predicting treatment response to omalizumab by performing whole blood transcriptional expression profiling using array and clinical data from GSE134544.

METHODS

We analyzed GSE134544 whole blood transcriptional and clinical data of omalizumab treatment using xCell, weighted gene co-expression network analysis (WGCNA), gene ontology enrichment analysis, KEGG pathway analysis, protein-protein interaction (PPI) network, and logistic regression analysis.

RESULTS

We calculated the immune enrichment score using xCell and found that CD4⁺ T cells, CD4⁺ Tem, CD4⁺ memory T cells, CD8⁺ Tcm, and dendritic cells (DC) were relatively higher in responders than in non-responders. Analysis of omalizumab response using WGCNA revealed that the above-mentioned significant immune cells in the red module was relevant to the sample traits; there were 547 genes in the red module. We identified 20 hub genes for the PPI network using cytoHubba, a Cytoscape plugin. Using logistic regression analysis, CD3E was found to be the only significant biomarker, and the area under the curve of ROC curves was 0.763.

CONCLUSION

CD3E maybe a new predictive biomarker of response to omalizumab treatment in asthma patients and be used to select more suitable asthma patients for omalizumab treatment.

Oral CorticoSteroid sparing with biologics in severe asthma: A remark of the Severe Asthma Network in Italy (SANI)

According to the data derived from several national and international registries, including SANI (Severe Asthma Network Italy), and considering the strong impact that frequent or regular use of oral corticosteroid has on quality of life (QoL) of severe asthmatics, as well as on the costs for managing corticosteroid-related diseases, oral corticosteroid sparing up to withdrawal should be considered a primary outcome in the management of severe asthma. New biologics have clearly demonstrated that this effect is possible, with concomitant reduction in the rate of exacerbations and in symptom control. Then, there is no reason for using so frequently oral corticosteroid before having explored all alternatives currently available for a large part of severe asthmatics.

How to compare the efficacy of biologic agents in asthma

OBJECTIVE

The use of biologics in severe asthma has made substantial strides in disease management and fostered a personalized medicine approach; however, how, when, and which biologic to choose are unresolved issues, which form the focus of this review.

DATA SOURCES

The data sources were published literature, including current guidelines, available through PubMed searches and online resources.

STUDY SELECTIONS

Studies and randomized controlled trials pertaining to the use of biologics in various phenotypes and/or endotypes of asthma and comparative analyses between biologics in asthma were included.

RESULTS

Inflammatory constructs in asthma are complex and translate differentially into clinical practice for both disease severity and treatment responsiveness. The utilization of biologics, which target selected components of inflammation, has begun to dramatically improve the course of management for many patients with severe asthma. A retuning of our approach into selecting appropriate patient cohorts or phenotypes for studies and selection of clinically relevant outcomes, which are reflected by existing and novel emerging biomarkers, is enabling a paradigm shift in asthma management. Comparing the efficacy of the available biologics for asthma is challenging as no direct head-to-head studies are available, and indirect comparisons to this query provide varying results.

CONCLUSION

Significant progress has been achieved in the management of severe asthma with treatment of target-specific biologics. Sophisticated algorithms and trial designs, using a combination of available biomarker profiles and clinical characteristics to stratify patient populations into more precise subphenotypes and endotypes to guide our choice of a biologic or therapy, are critically needed but currently not formulated.