Spontaneous sputum discriminates inflammatory phenotypes in patients with asthma

Asthma therapeutics: Past, present, and future

Asthma is a disease of airway inflammation and bronchial hyperresponsiveness affecting over 300 million individuals worldwide. Although described as early as 460 BC, the recognition of asthma as a disease, and the development and implementation of therapies to control it, emerged in the early 1900s. The subsequent century introduced the utilization of immunotherapy, inhaled medications, and anti-inflammatory corticosteroids for disease control. Since the beginning of the 21st century, however, the emergence of novel asthma pharmacotherapies has accelerated greatly. Our understanding of various asthma phenotypes and their underlying mechanisms (endotypes) has crystallized, leading to an era of precision medicine. Management strategies increasingly use targeted biologic medications aimed at interrupting key components of the inflammatory cascade. Monoclonal antibodies targeting the IgE, thymic stromal lymphopoietin, or interleukin-4, -5, and -13 pathways have revolutionized the care we provide our patients, resulting in a reduction in exacerbations and oral corticosteroid (OCS) dose, while improving lung function and asthma-related quality of life. Although they are able to provide relief for many sufferers of severe disease, and even remission in some, these biologic therapies are still in their infancy. Because their roles become further established, new therapeutic targets and modalities offer significant promise of an even greater personalized medicine approach. This review addresses historical standard-of-care strategies for asthma treatment, current recommendations, and a glimpse into future novel therapies that are likely to help millions worldwide. SIGNIFICANCE STATEMENT: Asthma affects hundreds of millions of individuals worldwide. In the last few decades, asthma treatment paradigms have transformed from recommendations to use anti-inflammatory and bronchodilatory inhalation-based therapies including corticosteroids and beta-agonists, to more precisely targeted add-on biologic therapies that employ monoclonal antibodies addressing specific mechanistic pathways associated with specific patient characteristics. Future therapies promise utilization of personalized medicine to a greater extent with novel therapeutic approaches to help improve the health and quality of life of those suffering from asthma.

Clinical Significance of Combined Detection of CCL22 and IL-1 as Potential New Bronchial Inflammatory Mediators in Children's Asthma

BACKGROUNDS

Severe asthma is a significant health burden because children with severe asthma are vulnerable to medication-related side effects, life-threatening deterioration, and impaired quality of life. However, there is a lack of data to elucidate the role of inflammatory variables in asthma. This study aimed to compare the levels of inflammatory factors in serum and sputum in children with acute and stable asthma to those in healthy children and the ability to predict clinical response to azithromycin therapy.

METHODS

This study recruited 95 individuals aged 1-3 years old and collected data from January 2018 to 2020. We examined serum and sputum inflammatory factors and constructed the least absolute shrinkage and selection operator (LASSO) model. Predictive models were constructed through multifactor logistic regression and presented in the form of column-line plots. The performance of the column-line diagrams was measured by subject work characteristics (ROC) curves, calibration plots, and decision curve analysis (DCA). Then, filter-paper samples were collected from 45 children with acute asthma who were randomly assigned to receive either azithromycin (10 mg/kg, n = 22) or placebo (n = 23). Pretreatment levels of immune mediators were then analyzed and compared with clinical response to azithromycin therapy.

RESULTS

Of the 95 eligible participants, 21 (22.11%) were healthy controls, 29 (30.53%) had stable asthma, and 45 (47.37%) had acute asthma. The levels of interferon-γ (IFN-γ), tumor necrosis factor-a (TNF-α), chemokine CCL22 (CCL22), interleukin 12 (IL-12), chemokine CCL4 (CCL4), chemokine CCL2 (CCL2), and chemokine CCL13 (CCL13）were significantly higher in the acute asthma group than in the stable asthma group. A logistic regression analysis was performed using CCL22 and IL-1 as independent variables. Additionally, IFN-γ, TNF-α, IL-1, IL-13, and CCL22 were identified in the LASSO model. Finally, we found that CCL22 and IL-1 were more responsive in predicting the response to azithromycin treatment.

CONCLUSION

Our results show that CCL22 and IL-1 are both representative markers during asthma symptom exacerbations and an immune mediator that can predict response to azithromycin therapy.

Decreased TLR7 expression was associated with airway eosinophilic inflammation and lung function in asthma: evidence from machine learning approaches and experimental validation

BACKGROUND

Asthma is a global public health concern. The underlying pathogenetic mechanisms of asthma were poorly understood. This study aims to explore potential biomarkers associated with asthma and analyze the pathological role of immune cell infiltration in the disease.

METHODS

The gene expression profiles of induced sputum were obtained from Gene Expression Omnibus datasets (GSE76262 and GSE137268) and were combined for analysis. Toll-like receptor 7 (TLR7) was identified as the core gene by the intersection of two different machine learning algorithms, namely, least absolute shrinkage and selector operation (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE), and the top 10 core networks based on Cytohubba. CIBERSORT algorithm was used to analyze the difference of immune cell infiltration between asthma and healthy control groups. Finally, the expression level of TLR7 was validated in induced sputum samples of patients with asthma.

RESULTS

A total of 320 differential expression genes between the asthma and healthy control groups were screened, including 184 upregulated genes and 136 downregulated genes. TLR7 was identified as the core gene after combining the results of LASSO regression, SVM-RFE algorithm, and top 10 hub genes. Significant differences were observed in the distribution of 13 out of 22 infiltrating immune cells in asthma. TLR7 was found to be closely related to the level of several infiltrating immune cells. TLR7 mRNA levels were downregulated in asthmatic patients compared with healthy controls (p = 0.0049). The area under the curve of TLR7 for the diagnosis of asthma was 0.7674 (95% CI 0.631-0.904, p = 0.006). Moreover, TLR7 mRNA levels were negatively correlated with exhaled nitric oxide fraction (r = - 0.3268, p = 0.0347) and the percentage of peripheral blood eosinophils (%) (r = - 0.3472, p = 0.041), and positively correlated with forced expiratory volume in the first second (FEV1) (% predicted) (r = 0.3960, p = 0.0071) and FEV1/forced vital capacity (r = 0.3213, p = 0.0314) in asthmatic patients.

CONCLUSIONS

Decreased TLR7 in the induced sputum of eosinophilic asthmatic patients was involved in immune cell infiltration and airway inflammation, which may serve as a new biomarker for the diagnosis of eosinophilic asthma.

Programmed Cell Death in Asthma: Apoptosis, Autophagy, Pyroptosis, Ferroptosis, and Necroptosis

Bronchial asthma is a complex heterogeneous airway disease, which has emerged as a global health issue. A comprehensive understanding of the different molecular mechanisms of bronchial asthma may be an efficient means to improve its clinical efficacy in the future. Increasing research evidence indicates that some types of programmed cell death (PCD), including apoptosis, autophagy, pyroptosis, ferroptosis, and necroptosis, contributed to asthma pathogenesis, and may become new targets for future asthma treatment. This review briefly discusses the molecular mechanism and signaling pathway of these forms of PCD focuses on summarizing their roles in the pathogenesis and treatment strategies of asthma and offers some efficient means to improve clinical efficacy of therapeutics for asthma in the near future.

Delineating asthma according to inflammation phenotypes with a focus on paucigranulocytic asthma

ABSTRACT

Asthma is characterized by chronic airway inflammation and airway hyper-responsiveness. However, the differences in pathophysiology and phenotypic symptomology make a diagnosis of "asthma" too broad hindering individualized treatment. Four asthmatic inflammatory phenotypes have been identified based on inflammatory cell profiles in sputum: eosinophilic, neutrophilic, paucigranulocytic, and mixed-granulocytic. Paucigranulocytic asthma may be one of the most common phenotypes in stable asthmatic patients, yet it remains much less studied than the other inflammatory phenotypes. Understanding of paucigranulocytic asthma in terms of phenotypic discrimination, distribution, stability, surrogate biomarkers, underlying pathophysiology, clinical characteristics, and current therapies is fragmented, which impedes clinical management of patients. This review brings together existing knowledge and ongoing research about asthma phenotypes, with a focus on paucigranulocytic asthma, in order to present a comprehensive picture that may clarify specific inflammatory phenotypes and thus improve clinical diagnoses and disease management.

Workup of difficult-to-treat asthma: implications from treatable traits

Traditional stepwise approach usually adjusts the treatment regimen based on changes in asthma symptoms and severity to achieve good asthma control. However, due to the generalized heterogeneity and complexity of asthma, its therapeutic efficacy in difficult-to-treat asthma is limited. Recently, a precision medicine approach based on the identification and intervention of treatable traits of chronic airway disease has been proposed and appears to be of greater benefit to asthmatics. We reported a 71-year-old male with uncontrolled asthma and multiple exacerbations over the past year. He complained of persistent dyspnea despite high-dose of inhaled corticosteroids plus other controllers. Does this patient have some potential treatable traits contributing to difficult-to-treat asthma? Through a multidimensional assessment of three domains including pulmonary, extrapulmonary, and behavioral/risk factors, 15 treatable traits were identified in the patient, mainly including airflow limitation, eosinophilic airway inflammation, small airway dysfunction, exacerbation prone, dilated cardiomyopathy, diabetes mellitus, inhaler device polypharmacy, smoking, and the absence of an asthma action plan. After targeted treatment for these treatable traits, the patient experienced significant improvement in dyspnea and he could maintain good asthma control with low-dose inhaled corticosteroids and long-acting β₂-agonist. This study shows that, in response to the limitation of a stepwise approach to therapy, treatable traits is a new strategy where patients are individually assessed for a specified set of treatable problems, and an individualized treatment program is developed and implemented based on this multidimensional assessment, especially for difficult-to-treat asthma.

HLA-G in asthma and its potential as an effective therapeutic agent

OBJECTIVE

Asthma is a heterogeneous disease. Severity of asthma and sensitivity to medications vary across asthma subtypes. Human leukocyte antigen (HLA)-G has a wide range of functions in normal and pathological physiology. Due to its powerful immune function, HLA-G participates in the pathogenesis of different asthma phenotypes by regulating the activity and function of various immune cells. The mechanism of HLA-G in asthma is not fully clear, and there is no consensus on its mechanism in asthma. Further studies are needed to explore the role of HLA-G in different phenotypes of human asthma.

METHODS

Observational study.

RESULTS

HLA-G is an important immunomodulatory factor in asthma. Studies have found different levels of HLA-G in patients with different asthma subtypes and healthy controls, but other studies have come to the opposite conclusion.

CONCLUSION

We speculate that further study on the mechanism of HLA-G in asthma pheno-types may explain some of the contradictions in current studies. Findings should provide information regarding the potential of HLA-G as a novel target for asthma diagnosis and treatment.

Using inflammatory index to distinguish asthma, asthma-COPD overlap and COPD: A retrospective observational study

BACKGROUND

Although asthma and chronic obstructive pulmonary disease (COPD) are two well-defined and distinct diseases, some patients present combined clinical features of both asthma and COPD, particularly in smokers and the elderly, a condition termed as asthma-COPD overlap (ACO). However, the definition of ACO is yet to be established and clinical guidelines to identify and manage ACO remain controversial. Therefore, in this study, inflammatory biomarkers were established to distinguish asthma, ACO, and COPD, and their relationship with the severity of patients' symptoms and pulmonary function were explored.

MATERIALS AND METHODS

A total of 178 patients, diagnosed with asthma (n = 38), ACO (n = 44), and COPD (n = 96) between January 2021 to June 2022, were enrolled in this study. The patients' pulmonary function was examined and routine blood samples were taken for the analysis of inflammatory indexes. Logistic regression analysis was used to establish inflammatory biomarkers for distinguishing asthma, ACO, and COPD; linear regression analysis was used to analyze the relationship between inflammatory indexes and symptom severity and pulmonary function.

RESULT

The results showed that, compared with ACO, the higher the indexes of platelet, neutrophil-lymphocyte ratio (NLR) and eosinophil-basophil ratio (EBR), the more likely the possibility of asthma and COPD in patients, while the higher the eosinophils, the less likely the possibility of asthma and COPD. Hemoglobin and lymphocyte-monocyte ratio (LMR) were negatively correlated with the severity of patients' symptoms, while platelet-lymphocyte ratio (PLR) was negatively correlated with forced expiratory volume in the 1 s/forced vital capacity (FEV1/FVC) and FEV1 percent predicted (% pred), and EBR was positively correlated with FEV1% pred.

CONCLUSION

Inflammatory indexes are biomarkers for distinguishing asthma, ACO, and COPD, which are of clinical significance in therapeutic strategies and prognosis evaluation.

Immunosenescence, Inflammaging, and Lung Senescence in Asthma in the Elderly

Prevalence of asthma in older adults is growing along with increasing global life expectancy. Due to poor clinical consequences such as high mortality, advancement in understanding the pathophysiology of asthma in older patients has been sought to provide prompt treatment for them. Age-related alterations of functions in the immune system and lung parenchyma occur throughout life. Alterations with advancing age are promoted by various stimuli, including pathobionts, fungi, viruses, pollutants, and damage-associated molecular patterns derived from impaired cells, abandoned cell debris, and senescent cells. Age-related changes in the innate and adaptive immune response, termed immunosenescence, includes impairment of phagocytosis and antigen presentation, enhancement of proinflammatory mediator generation, and production of senescence-associated secretory phenotype. Immnunosenescence could promote inflammaging (chronic low-grade inflammation) and contribute to late-onset adult asthma and asthma in the elderly, along with age-related pulmonary disease, such as chronic obstructive pulmonary disease and pulmonary fibrosis, due to lung parenchyma senescence. Aged patients with asthma exhibit local and systemic type 2 and non-type 2 inflammation, associated with clinical manifestations. Here, we discuss immunosenescence’s contribution to the immune response and the combination of type 2 inflammation and inflammaging in asthma in the elderly and present an overview of age-related features in the immune system and lung structure.

Treatment Resistance in Severe Asthma Patients With a Combination of High Fraction of Exhaled Nitric Oxide and Low Blood Eosinophil Counts

Background: Combining a fraction of exhaled nitric oxide (FeNO) and blood eosinophil count (B-EOS) may be a useful strategy for administration of biologics such as anti-IgE or anti-IL-5 to patients with type 2 inflammatory-predominant severe asthma and is important to be elucidated considering the increasing use of biologics.

Methods: This cross-sectional study analyzed the clinical data from 114 adult patients with severe asthma, who were treated at Saitama Medical University Hospital. The eligible patients were stratified into four subgroups defined by thresholds of FeNO and blood eosinophil (B-EOS) counts to detect sputum eosinophilia, using the receiver operating characteristic curve analysis. A total of 75 patients with optimal samples were stratified into four subtypes defined by thresholds of sputum eosinophilia and neutrophilia. Clinical characteristics, pattern of biologics, and distribution of sputum subtypes were analyzed in the stratified subclasses according to the FeNO and B-EOS thresholds. The asthma exacerbation (AE)-free time of the FeNO/B-EOS subgroups and any biologics treatment including anti-IgE or anti-IL-5 use were examined using the Kaplan–Meier method. The hazard ratios (HRs) for AE-free time were examined using the Cox proportional hazard model.

Results: The optimal cutoff values for prediction of sputum eosinophilia were defined as ≥2.7% wherein for FeNO as ≥27 ppb and B-EOS as ≥265/µL were considered. The high-FeNO subgroups showed significant high total IgE, compared with the low FeNO. The high-FeNO/high-B-EOS and the high-FeNO/low-B-EOS subgroups showed the largest prevalence of mepolizumab and benralizumab use among the other FeNO/B-EOS, respectively. The high-FeNO/low-B-EOS showed the largest frequency of AEs, high HR, and the shortest AE-free time, among the other FeNO/B-EOS. The sputum eosinophil-predominant subtype was the great majority in the high FeNO/high B-EOS. A diverse distribution of sputum leukocyte-predominant subtype was observed in the other FeNO/B-EOS. The subsequent AE-free time and its HR were comparable among the biologics use groups.

Conclusion: The strategy of classifying severe asthma based on the combination of FeNO and B-EOS proposes particular refractory type 2 severe asthma and underlying airway inflammation as a feasible trait for optimal biologics use.

Metabolic Phenotypes in Asthmatic Adults: Relationship with Inflammatory and Clinical Phenotypes and Prognostic Implications

Bronchial asthma is a chronic disease that affects individuals of all ages. It has a high prevalence and is associated with high morbidity and considerable levels of mortality. However, asthma is not a single disease, and multiple subtypes or phenotypes (clinical, inflammatory or combinations thereof) can be detected, namely in aggregated clusters. Most studies have characterised asthma phenotypes and clusters of phenotypes using mainly clinical and inflammatory parameters. These studies are important because they may have clinical and prognostic implications and may also help to tailor personalised treatment approaches. In addition, various metabolomics studies have helped to further define the metabolic features of asthma, using electronic noses or targeted and untargeted approaches. Besides discriminating between asthma and a healthy state, metabolomics can detect the metabolic signatures associated with some asthma subtypes, namely eosinophilic and non-eosinophilic phenotypes or the obese asthma phenotype, and this may prove very useful in point-of-care application. Furthermore, metabolomics also discriminates between asthma and other “phenotypes” of chronic obstructive airway diseases, such as chronic obstructive pulmonary disease (COPD) or Asthma–COPD Overlap (ACO). However, there are still various aspects that need to be more thoroughly investigated in the context of asthma phenotypes in adequately designed, homogeneous, multicentre studies, using adequate tools and integrating metabolomics into a multiple-level approach.