Sputum biomarkers during aspirin desensitization in nonsteroidal anti-inflammatory drugs exacerbated respiratory disease

Non‐eosinophilic asthma in nonsteroidal anti‐inflammatory drug exacerbated respiratory disease

Background

The cellular inflammatory pattern of nonsteroidal anti‐inflammatory drug–exacerbated respiratory disease (N‐ERD) is heterogeneous. However, data on the heterogeneity of non‐eosinophilic asthma (NEA) with aspirin hypersensitivity are scanty. By examination of N‐ERD patients based on clinical data and eicosanoid biomarkers we aimed to identify NEA endotypes potentially guiding clinical management.

Methods

Induced sputum was collected from patients with N‐ERD. Sixty six patients (49.6% of 133 N‐ERD) with NEA were included in the hierarchical cluster analysis based on clinical and laboratory data. The quality of clustering was evaluated using internal cluster validation with different indices and a practical decision tree was proposed to simplify stratification of patients.

Results

The most frequent NEA pattern was paucigranulocytic (PGA; 75.8%), remaining was neutrophilic asthma (NA; 24.2%). Four clusters were identified. Cluster #3 included the highest number of NEA patients (37.9%) with severe asthma and PGA pattern (96.0%). Cluster #1 (24.2%) included severe only asthma, with a higher prevalence of NA (50%). Cluster #2 (25.8%) comprised well‐controlled mild or severe asthma (PGA; 76.5%). Cluster #4 contained only 12.1% patients with well‐controlled moderate asthma (PGA; 62.5%). Sputum prostaglandin D₂ levels distinguished cluster #1 from the remaining clusters with an area under the curve of 0.94.

Conclusions

Among identified four NEA subtypes, clusters #3 and #1 represented N‐ERD patients with severe asthma but a different inflammatory signatures. All the clusters were discriminated by sputum PGD₂ levels, asthma severity, and age of patients. The heterogeneity of non‐eosinophilic N‐ERD suggests a need for novel targeted interventions.

What happens to basophils and tryptase, LXA4 and CysLTs during aspirin desensitization?

INTRODUCTION

Aspirin desensitization (AD) is an effective treatment in patients with non-steroidal anti-inflammatory drugs (NSAID)-exacerbated respiratory disease (NERD) by providing inhibitory effect on symptoms and polyp recurrence. However, limited data is available on how AD works. We aimed to study comprehensively the mechanisms underlying AD by examining basophil activation (CD203c upregulation), mediator-releases of tryptase, CysLT, and LXA₄, and LTB₄ receptor expression for the first 3 months of AD.

METHODS

The study was conducted in patients with NERD who underwent AD (group 1: n = 23), patients with NERD who received no desensitization (group 2: n = 22), and healthy volunteers (group 3, n = 13). All participants provided blood samples for flow cytometry studies (CD203c and LTB₄ receptor), and mediator releases (CysLT, LXA_4, and tryptase) for the relevant time points determined.

RESULTS

All baseline parameters of CD203c and LTB₄ receptor expressions, tryptase, CysLT, and LXA₄ releases were similar in each group (p > 0.05). In group 1, CD203c started to be upregulated at the time of reactions during AD, and continued to be high for 3 months when compared to controls. All other study parameters were comparable with baseline and at the other time points in each group (p > 0.05).

CONCLUSION

Although basophils are active during the first 3 months of AD, no releases of CysLT, tryptase or LXA₄ exist. Therefore, our results suggest that despite active basophils, inhibition of mediators can at least partly explain underlying the mechanism in the first three months of AD.

Machine learning in the diagnosis of asthma phenotypes during coronavirus disease 2019 pandemic

Background

During the coronavirus disease 2019 (COVID‐19) pandemic, it has become a pressing need to be able to diagnose aspirin hypersensitivity in patients with asthma without the need to use oral aspirin challenge (OAC) testing. OAC is time consuming and is associated with the risk of severe hypersensitive reactions. In this study, we sought to investigate whether machine learning (ML) based on some clinical and laboratory procedures performed during the pandemic might be used for discriminating between patients with aspirin hypersensitivity and those with aspirin‐tolerant asthma.

Methods

We used a prospective database of 135 patients with non‐steroidal anti‐inflammatory drug (NSAID)–exacerbated respiratory disease (NERD) and 81 NSAID‐tolerant (NTA) patients with asthma who underwent OAC. Clinical characteristics, inflammatory phenotypes based on sputum cells, as well as eicosanoid levels in induced sputum supernatant and urine were extracted for the purpose of applying ML techniques.

Results

The overall best ML model, neural network (NN), trained on a set of best features, achieved a sensitivity of 95% and a specificity of 76% for diagnosing NERD. The 3 promising models (i.e., multiple logistic regression, support vector machine, and NN) trained on a set of easy‐to‐obtain features including only clinical characteristics and laboratory data achieved a sensitivity of 97% and a specificity of 67%.

Conclusions

ML techniques are becoming a promising tool for discriminating between patients with NERD and NTA. The models are easy to use, safe, and achieve very good results, which is particularly important during the COVID‐19 pandemic.

Local and Systemic Production of Pro-Inflammatory Eicosanoids Is Inversely Related to Sensitization to Aeroallergens in Patients with Aspirin-Exacerbated Respiratory Disease

Aspirin-exacerbated respiratory disease (AERD) is characterized by overproduction of the pro-inflammatory eicosanoids. Although immunoglobulin E-mediated sensitization to aeroallergens is common among AERD patients, it does not belong to the defining disease characteristics. In this study of 133 AERD patients, we sought to find a relationship between sensitization to aeroallergens and local (leukotriene E₄, prostaglandin E₂ and prostaglandin D₂) and/or systemic (leukotriene E₄) production of arachidonic acid metabolites. Interestingly, a negative association between pro-inflammatory eicosanoid levels in induced sputum supernatant or urine and sensitization to aeroallergens was observed. This inverse relationship might suggest the presence of a protective effect of atopic sensitization to aeroallergens against stronger local airway inflammation and higher systemic AERD-related inflammatory activity.

Emerging Biomarkers Beyond Leukotrienes for the Management of Nonsteroidal Anti-inflammatory Drug (NSAID)-Exacerbated Respiratory Disease

Nonsteroidal anti-inflammatory drug (NSAID)-exacerbated respiratory disease (NERD) is a unique condition characterized by aspirin/NSAID hypersensitivity, adult-onset asthma, and/or chronic rhinosinusitis with nasal polyps. Arachidonic acid metabolism dysregulation and intense eosinophilic/type 2 inflammation are central mechanisms in NERD. Studies have been conducted on various biomarkers, and urinary leukotriene E4 is considered the most available biomarker of NERD. However, the pathophysiology of NERD is heterogeneous and complex. Epithelial cells and platelets can interact with immune cells in NERD, and novel biomarkers related to these interactions have recently been investigated. We summarize emerging novel biomarkers of NERD and discuss their roles in the management of NERD.

Biomarkers for predicting response to aspirin therapy in aspirin-exacerbated respiratory disease

Background

Aspirin desensitization followed by daily aspirin use is an effective treatment for aspirin‐exacerbated respiratory disease (AERD).

Objective

To assess clinical features as well as genetic, immune, cytological and biochemical biomarkers that might predict a positive response to high‐dose aspirin therapy in AERD.

Methods

We enrolled 34 AERD patients with severe asthma who underwent aspirin desensitization followed by 52‐week aspirin treatment (650 mg/d). At baseline and at 52 weeks, clinical assessment was performed; phenotypes based on induced sputum cells were identified; eicosanoid, cytokine and chemokine levels in induced sputum supernatant were determined; and induced sputum expression of 94 genes was assessed. Responders to high‐dose aspirin were defined as patients with improvement in 5‐item Asthma Control Questionnaire score, 22‐item Sino‐Nasal Outcome Test (SNOT‐22) score and forced expiratory volume in 1 second at 52 weeks.

Results

There were 28 responders (82%). Positive baseline predictors of response included female sex (p = .002), higher SNOT‐22 score (p = .03), higher blood eosinophil count (p = .01), lower neutrophil percentage in induced sputum (p = .003), higher expression of the hydroxyprostaglandin dehydrogenase gene, HPGD (p = .004) and lower expression of the proteoglycan 2 gene, PRG2 (p = .01). The best prediction model included Asthma Control Test and SNOT‐22 scores, blood eosinophils and total serum immunoglobulin E. Responders showed a marked decrease in sputum eosinophils but no changes in eicosanoid levels.

Conclusions and Clinical Relevance

Female sex, high blood eosinophil count, low sputum neutrophil percentage, severe nasal symptoms, high HPGD expression and low PRG2 expression may predict a positive response to long‐term high‐dose aspirin therapy in patients with AERD.

The Role of Mast Cells in Aspirin-Exacerbated Respiratory Disease (AERD) Pathogenesis: Implications for Future Therapeutics

Mast cells (MC) have recently been demonstrated to play an integral role in the pathogenesis of aspirin-exacerbated respiratory disease (AERD). When activated, MCs release pre-formed granules of many pro-inflammatory mediators, including histamine, serotonin, and various chemokines and cytokines including tumor necrosis factor (TNF)-α, interferon ɣ (IFN ɣ), macrophage inhibitory factor, transforming growth factor, interleukin (IL) 1, 3–6, 9, 10, 13 and 16. These mediators promote inflammation in AERD by recruiting or activating a network of cells involved in acute and chronic inflammatory pathways, such as endothelial, epithelial, stromal, and other immune cells. Several studies have implicated multifactorial pathways for MC activation in AERD beyond classical IgE mediated mechanisms. The elucidation of these complex networks therefore represents important targets for innovative patient therapeutics. This review summarizes classic and alternative pathways of MC activation in AERD with a special focus in relation to new and emerging treatment strategies.

Artificial neural network identifies nonsteroidal anti-inflammatory drugs exacerbated respiratory disease (N-ERD) cohort

Background

To date, there has been no reliable in vitro test to either diagnose or differentiate nonsteroidal anti‐inflammatory drug (NSAID)–exacerbated respiratory disease (N‐ERD). The aim of the present study was to develop and validate an artificial neural network (ANN) for the prediction of N‐ERD in patients with asthma.

Methods

This study used a prospective database of patients with N‐ERD (n = 121) and aspirin‐tolerant (n = 82) who underwent aspirin challenge from May 2014 to May 2018. Eighteen parameters, including clinical characteristics, inflammatory phenotypes based on sputum cells, as well as eicosanoid levels in induced sputum supernatant (ISS) and urine were extracted for the ANN.

Results

The validation sensitivity of ANN was 94.12% (80.32%‐99.28%), specificity was 73.08% (52.21%‐88.43%), and accuracy was 85.00% (77.43%‐92.90%) for the prediction of N‐ERD. The area under the receiver operating curve was 0.83 (0.71‐0.90).

Conclusions

The designed ANN model seems to have powerful prediction capabilities to provide diagnosis of N‐ERD. Although it cannot replace the gold‐standard aspirin challenge test, the implementation of the ANN might provide an added value for identification of patients with N‐ERD. External validation in a large cohort is needed to confirm our results.

Endoscopic sinus surgery improves aspirin treatment response in aspirin-exacerbated respiratory disease patients

BACKGROUND

Aspirin desensitization and treatment benefits most patients with aspirin-exacerbated respiratory disease (AERD), although some patients fail therapy. Our objective was to assess whether recent endoscopic sinus surgery (ESS) improved aspirin treatment outcomes in AERD patients who initially failed aspirin therapy.

METHODS

Outcomes of aspirin desensitization and treatment in AERD patients prospectively enrolled were assessed preoperatively and at 4, 12, and 24 weeks after ESS by determining changes in Asthma Control Test (ACT) and Rhinoconjunctivitis Quality of Life Questionnaire (RQLQ) scores and respiratory function. Biomarkers, including fractional excretion of nitric oxide (FeNO), spirometry, nasal inspiratory peak flow (NPF), immunoglobulin E (IgE), and eosinophil count, were measured.

RESULTS

Nineteen patients who benefited (responders) and 21 patients who failed (nonresponders) preoperative aspirin treatment with a distant history of ESS (mean, 48 months) were identified. Nonresponders were more likely to be African American (71%, p < 0.01) and have higher baseline IgE levels (252 kU/L vs 87 kU/L in responders, p < 0.01). 24 of the 40 patients (nine responders and 15 non-responders) required subsequent ESS and underwent another aspirin desensitization 3-4 weeks after ESS. All 24 patients tolerated a second round of aspirin desensitization and treatment. The primary aspirin therapy was associated with a significant increase in IgE in nonresponders, but there was no significant increase in IgE after the second aspirin desensitization and treatment.

CONCLUSION

Antecedent ESS enhances aspirin treatment responses in AERD patients and may convert patients who failed aspirin treatment before surgery to a more responsive phenotype after ESS. Patients with higher baseline serum IgE levels may benefit from ESS performed shortly before aspirin desensitization and therapy.