Machine learning implicates the IL-18 signaling axis in severe asthma

Exploring the molecular mechanisms of asthma across multiple datasets

BACKGROUND

Asthma, a prevalent chronic respiratory disorder, remains enigmatic, notwithstanding considerable advancements in our comprehension. Continuous efforts are crucial for discovering novel molecular targets and gaining a comprehensive understanding of its pathogenesis.

MATERIALS AND METHODS

In this study, we analyzed gene expression data from 212 individuals, including asthma patients and healthy controls, to identify 267 differentially expressed genes, among which C1orf64 and C7orf26 emerged as potential key genes in asthma pathogenesis. Various bioinformatics tools, including differential gene expression analysis, pathway enrichment, drug target prediction, and single-cell analysis, were employed to explore the potential roles of the genes.

RESULTS

Quantitative PCR demonstrated differential expression of C1orf64 and C7orf26 in the asthmatic airway epithelial tissue, implying their potential involvement in asthma pathogenesis. GSEA enrichment analysis revealed significant enrichment of these genes in signaling pathways associated with asthma progression, such as ABC transporters, cell cycle, CAMs, DNA replication, and the Notch signaling pathway. Drug target prediction, based on upregulated and downregulated differential expression, highlighted potential asthma treatments, including Tyrphostin-AG-126, Cephalin, Verrucarin-a, and Emetine. The selection of these drugs was based on their significance in the analysis and their established anti-inflammatory and antiviral invasion properties. Utilizing Seurat and Celldex packages for single-cell sequencing analysis unveiled disease-specific gene expression patterns and cell types. Expression of C1orf64 and C7orf26 in T cells, NK cells, and B cells, instrumental in promoting hallmark features of asthma, was observed, suggesting their potential influence on asthma development and progression.

CONCLUSION

This study uncovers novel genetic aspects of asthma, highlighting potential therapeutic pathways. It exemplifies the power of integrative bioinformatics in decoding complex disease patterns. However, these findings require further validation, and the precise roles of C1orf64 and C7orf26 in asthma warrant additional investigation to validate their therapeutic potential.

Asthma Pathogenesis: Phenotypes, Therapies, and Gaps: Summary of the Aspen Lung Conference 2023

Although substantial progress has been made in our understanding of asthma pathogenesis and phenotypes over the nearly 60-year history of the Aspen Lung Conferences on asthma, many ongoing challenges exist in our understanding of the clinical and molecular heterogeneity of the disease and an individual patient's response to therapy. This report summarizes the proceedings of the 2023 Aspen Lung Conference, which was organized to review the clinical and molecular heterogeneity of asthma and to better understand the impact of genetic, environmental, cellular, and molecular influences on disease susceptibility, heterogeneity, and severity. The goals of the conference were to review new information about asthma phenotypes, cellular processes, and cellular signatures underlying disease heterogeneity and treatment response. The report concludes with ongoing gaps in our understanding of asthma pathobiology and provides some recommendations for future research to better understand the clinical and basic mechanisms underlying disease heterogeneity in asthma and to advance the development of new treatments for this growing public health problem.

Low Serum IL-18 Levels May Predict the Effectiveness of Dupilumab in Severe Asthma

Objective Dupilumab, a monoclonal antibody specific for the human interleukin (IL)-4 receptor α, is used to treat severe asthma, especially in patients with elevated blood eosinophil counts and fractional exhaled nitric oxide (FeNO). The therapeutic response to dupilumab is highly variable. In this study, we explored new serum biomarkers to accurately predict the effect of dupilumab and examine the effect of dupilumab based on changes in the clinical parameters and cytokine levels. Methods Seventeen patients with severe asthma treated with dupilumab were enrolled. Responders, defined as those with a >0.5-point decrease in the Asthma Control Questionnaire (ACQ) score after 6 months of treatment, were included. Results There were 10 responders and 7 non-responders. Serum type 2 cytokines were equivalent between responders and non-responders; the baseline serum IL-18 level was significantly lower in responders than in non-responders (responders, 194.9±51.0 pg/mL; non-responders, 323.4±122.7 pg/mL, p=0.013). The cut-off value of IL-18 at 230.5 pg/mL could be used to distinguish non-responders from responders (sensitivity 71.4, specificity 80.0, p=0.032). Conclusion A low baseline serum IL-18 level may be a useful predictor of an unfavorable response to dupilumab in terms of the ACQ-6.

IL18R1-Related Molecules as Biomarkers for Asthma Severity and Prognostic Markers for Idiopathic Pulmonary Fibrosis

To determine the role of inflammation-related proteins in predicting asthma severity and outcome, 92 inflammation-related proteins were measured in the asthmatic serum using Olink analysis. Different bioinformatics algorithms were developed to cross analyze with the single-cell or transcriptome data sets from the Gene Expression Omnibus database to explore the role of IL18R1 and related genes in asthma and idiopathic pulmonary fibrosis (IPF). Olink identified 52 differentially expressed proteins in asthma. They were strongly linked to the cytokine-cytokine receptor interaction, TNF, and NF-κB signaling pathway. Seven proteins were found in both single-cell RNA and Olink analyses. Among them, IL18R1 was predominantly expressed in mast cells, and the results suggested enhanced communication between mast cells and CD 8+ T cells. IL18R1 was upregulated in serum and induced sputum and bronchoalveolar lavage fluid of patients with uncontrolled or severe asthma. IL18R1 was positively correlated with TNFSF1 and OSM and S100A12. The diagnostic efficacy of these serum IL18R1-related molecules for asthma ranged from 0.839 to 0.921. Moreover, high levels of IL18R1, TNFSF1, OSM, and S100A12 were significantly associated with shorter survival times and worse lung function. IL18R1-related molecules may serve as biomarkers for monitoring uncontrolled or severe asthma and as prognostic markers for IPF.

Distinct Epithelial-Innate Immune Cell Transcriptional Circuits Underlie Airway Hyperresponsiveness in Asthma

Rationale: Indirect airway hyperresponsiveness (AHR) is a highly specific feature of asthma, but the underlying mechanisms responsible for driving indirect AHR remain incompletely understood. Objectives: To identify differences in gene expression in epithelial brushings obtained from individuals with asthma who were characterized for indirect AHR in the form of exercise-induced bronchoconstriction (EIB). Methods: RNA-sequencing analysis was performed on epithelial brushings obtained from individuals with asthma with EIB (n = 11) and without EIB (n = 9). Differentially expressed genes (DEGs) between the groups were correlated with measures of airway physiology, sputum inflammatory markers, and airway wall immunopathology. On the basis of these relationships, we examined the effects of primary airway epithelial cells (AECs) and specific epithelial cell-derived cytokines on both mast cells (MCs) and eosinophils (EOS). Measurements and Main Results: We identified 120 DEGs in individuals with and without EIB. Network analyses suggested critical roles for IL-33-, IL-18-, and IFN-γ-related signaling among these DEGs. IL1RL1 expression was positively correlated with the density of MCs in the epithelial compartment, and IL1RL1, IL18R1, and IFNG were positively correlated with the density of intraepithelial EOS. Subsequent ex vivo modeling demonstrated that AECs promote sustained type 2 (T2) inflammation in MCs and enhance IL-33-induced T2 gene expression. Furthermore, EOS increase the expression of IFNG and IL13 in response to both IL-18 and IL-33 as well as exposure to AECs. Conclusions: Circuits involving epithelial interactions with MCs and EOS are closely associated with indirect AHR. Ex vivo modeling indicates that epithelial-dependent regulation of these innate cells may be critical in indirect AHR and modulating T2 and non-T2 inflammation in asthma.

Bronchial epithelial cell transcriptional responses to inhaled corticosteroids dictate severe asthmatic outcomes

BACKGROUND

Inhaled corticosteroids (CSs) are the backbone of asthma treatment, improving quality of life, exacerbation rates, and mortality. Although effective for most, a subset of patients with asthma experience CS-resistant disease despite receiving high-dose medication.

OBJECTIVE

We sought to investigate the transcriptomic response of bronchial epithelial cells (BECs) to inhaled CSs.

METHODS

Independent component analysis was performed on datasets, detailing the transcriptional response of BECs to CS treatment. The expression of these CS-response components was examined in 2 patient cohorts and investigated in relation to clinical parameters. Supervised learning was used to predict BEC CS responses using peripheral blood gene expression.

RESULTS

We identified a signature of CS response that was closely correlated with CS use in patients with asthma. Participants could be separated on the basis of CS-response genes into groups with high and low signature expression. Patients with low expression of CS-response genes, particularly those with a severe asthma diagnosis, showed worse lung function and quality of life. These individuals demonstrated enrichment for T-lymphocyte infiltration in endobronchial brushings. Supervised machine learning identified a 7-gene signature from peripheral blood that reliably identified patients with poor CS-response expression in BECs.

CONCLUSIONS

Loss of CS transcriptional responses within bronchial epithelium was related to impaired lung function and poor quality of life, particularly in patients with severe asthma. These individuals were identified using minimally invasive blood sampling, suggesting these findings may enable earlier triage to alternative treatments.

Challenges in severe asthma: Do we need new drugs or new biomarkers?

Severe asthma is a complex, heterogenous airway condition. There have been significant advances in severe asthma management in the past decade using monoclonal antibody therapies that target the inflammatory component of the disease. Patient selection has been paramount for the success of these biologicals, leading to significant interest in biomarkers to guide treatment. Some severe asthmatics remain suboptimally controlled despite trials of biologicals and many of these patients still require chronic systemic corticosteroids. New therapeutics are currently in development to address this unmet need. However, whether these patients could be better treated by using novel biomarkers that inform selection among currently available biologics, and that objectively measure disease control is unclear. In this review, we examine the currently used biomarkers that guide severe asthma management and emerging biomarkers that may improve asthma therapy in the future.

Advancing Lung Immunology Research: An Official American Thoracic Society Workshop Report

The mammalian airways and lungs are exposed to a myriad of inhaled particulate matter, allergens, and pathogens. The immune system plays an essential role in protecting the host from respiratory pathogens, but a dysregulated immune response during respiratory infection can impair pathogen clearance and lead to immunopathology. Furthermore, inappropriate immunity to inhaled antigens can lead to pulmonary diseases. A complex network of epithelial, neural, stromal, and immune cells has evolved to sense and respond to inhaled antigens, including the decision to promote tolerance versus a rapid, robust, and targeted immune response. Although there has been great progress in understanding the mechanisms governing immunity to respiratory pathogens and aeroantigens, we are only beginning to develop an integrated understanding of the cellular networks governing tissue immunity within the lungs and how it changes after inflammation and over the human life course. An integrated model of airway and lung immunity will be necessary to improve mucosal vaccine design as well as prevent and treat acute and chronic inflammatory pulmonary diseases. Given the importance of immunology in pulmonary research, the American Thoracic Society convened a working group to highlight central areas of investigation to advance the science of lung immunology and improve human health.

Differences in Inflammatory Cytokine Profile in Obesity-Associated Asthma: Effects of Weight Loss

Obesity and asthma are associated with systemic inflammation maintained by mediators released by adipose tissue and lung. This study investigated the inflammatory serum mediator profile in obese subjects (O) (n = 35), non-obese asthma (NOA) patients (n = 14), obese asthmatics (OA) (n = 21) and healthy controls (HC) (n = 33). The effect of weight loss after bariatric surgery (BS) was examined in 10 OA and 31 O subjects. We analyzed serum markers including leptin, adiponectin, TGF-β1, TNFR2, MCP-1, ezrin, YKL-40, ST2, IL-5, IL-9, and IL-18. Compared with HC subjects, the O group showed increased levels of leptin, TGF-β1, TNFR2, MCP-1, ezrin, YKL-40, and ST2; the OA group presented increased levels of MCP-1, ezrin, YKL-40, and IL-18, and the NOA group had increased levels of ezrin, YKL-40, IL-5, and IL-18. The higher adiponectin/leptin ratio in NOA with respect to OA subjects was the only significant difference between the two groups. IL-9 was the only cytokine with significantly higher levels in OA with respect to O subjects. TNFR2, ezrin, MCP-1, and IL-18 concentrations significantly decreased in O subjects after BS. O, OA, and NOA showed distinct patterns of systemic inflammation. Leptin and adiponectin are regulated in asthma by obesity-dependent and -independent mechanisms. Combination of asthma and obesity does not result in significant additive effects on circulating cytokine levels.