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Gene signature profiles in whole blood cells from severe asthma patinets treated with benralizumab

ABSTRACT: Severe asthma is a clinically and physiologically heterogeneous disease. Benralizumab is a monoclonal antibody which binds the alpha chain of the interleukin-5 receptor and used for severe eosinophilic asthma worldwide. However, not all eosinophilic asthma patients will benefit from benralizumab due to heterogeneity of this disease. Therefore, we performed comprehensive gene expression analysis of whole blood cells that examine severe asthma disease heterogeneity in response to benralizumab. This study is the first to perform comprehensive transcriptome analysis of whole blood cells to identify transcriptomic endotypes of severe asthma clusters that correlate with benralizumab response. The identified transcriptomic endotypes of severe asthma clusters are associated with gene signatures of eosinophils and neutrophilis.

ORGANISM(S): Homo sapiens

PROVIDER: GSE148725 | GEO | 2023/04/15

REPOSITORIES: GEO

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Project description:BACKGROUND: Evaluation of the airway transcriptome may reveal patterns of gene expression that are associated with clinical phenotypes of asthma. To define transcriptomic endotypes of asthma (TEA) we analyzed gene expression in induced sputum that correlate with phenotypes of disease. METHODS: Gene expression was measured in sputum of subjects with asthma using Affymetrix HuGene ST 1.0 microarrays. Unsupervised clustering analysis of genes in pathways selected from the Kyoto Encyclopedia of Genes and Genomes (KEGG) identified TEA clusters. Clinical characteristics were compared and logistic regression analysis of matched blood samples defined an expression profile to determine the TEA cluster assignment in a cohort of children with asthma for validation. RESULTS: Three TEA clusters were identified. TEA cluster 1 had the most subjects with a history of intubation (P = 0.05), a lower pre-bronchodilator FEV1 (P = 0.006), a higher bronchodilator response (P = 0.03), and higher exhaled nitric oxide levels (P = 0.04), compared to the other TEA clusters. TEA cluster 2, the smallest cluster had the most subjects that were hospitalized for asthma (P = 0.04). Subjects in TEA cluster 3, the largest cluster, had normal lung function, low exhaled nitric oxide levels, and lower inhaled steroid requirements. Evaluation of TEA clusters in children confirmed that TEA clusters 1 and 2 are associated with a history of intubation (P = 5.58 x 10-06) and hospitalization (P = 0.01), respectively. CONCLUSIONS: Patterns of gene expression in the sputum and blood reveal TEA clusters that are associated with severe asthma phenotypes in children and adults. Gene expression was measured in sputum of subjects with asthma using Affymetrix HuGene ST 1.0 microarrays. Unsupervised clustering analysis of genes in pathways selected from the Kyoto Encyclopedia of Genes and Genomes (KEGG) identified TEA clusters. Clinical characteristics were compared and logistic regression analysis of matched blood samples defined an expression profile to determine the TEA cluster assignment in a cohort of children with asthma for validation.

Project description:Asthma is an inflammatory disease of the airways characterised by episodic airway obstruction resulting in cough, episodic shortness of breath. It is, and is clinically and physiologically heterogeneous. It is estimated that around 300 million people worldwide have the diseaseare diagnosed with asthma, including up to 20% of children (Asher et al, 2006), with 5–10% of these children believed to have severe or difficult-to-treat asthma. Asthma has often been classified in terms of severity and based on clinical diagnostic criteria, but it is now apparent that the heterogeneity that exists at the physiological level is also a feature of the underlying pathological mechanisms (Lotvall et al, 2011). The aim of this study was to identify blood transcriptomics profiles for children diagnosed with asthma or wheeze, and establish whether these profiles suggested endotypes or mechanisms that could underlie disease, or be related to disease severity, in these children. Importantly, given that children are currently treated with the same medicines as adults, we also aimed to compare profiles of children to those of adults with asthma to help determine whether efforts should be directed to the development of medicines targeting pathways and mechanisms that may be unique to children. To this end, we used gene transcriptome data generated from blood samples from adults and children from the U-BIOPRED consortium to ask how similar or different the differential gene expression profiles were between groups of adults and pre-school or school-aged children with severe or mild-moderate asthma (or wheeze for the pre-school aged children) using current definitions. The Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) project was set up as a public-private partnership within the framework of the Innovative Medicines Initiative (IMI), engaging academia, the pharmaceutical industry and patient groups. The goal of this investigation was to identify transcript fingerprints in whole blood that characterize patients with severe asthma and to determine whether subgroups of severe asthmatics can be identified.

Project description:Asthma is a complex, chronic respiratory disease with marked clinical and pathophysiological heterogeneity. Distinct inflammatory phenotypes of eosinophilic, mixed, neutrophilic and paucigranulocytic asthma are identified in patients, but most in vivo mouse models, studying asthma mechanisms, mimic only eosinophilic phenotype in humans. The detailed unbiased in vivo studies on molecular responses among different kinds of inflammation in asthma models are lacking. Therefore, we developed mouse models representing three different inflammatory phenotypes of airway inflammation, namely eosinophilic, mixed, and neutrophilic asthma via different methods of house dust mite sensitisation. We used microarrays to determine the global gene expression in the lungs of mice with eosinophilic, mixed and neutrophilic inflammatory phenotypes to uncover underlying differences in clinical presentation and to find novel molecular targets and pathways, which might reflect different molecular mechanisms of the disease. By whole genome transcriptome profiling, we found that airway tight junction (TJ) molecules, mucins and inflammasome-related genes are differentially expressed in distinct phenotypes of allergic airway inflammation. Next, detailed analysis of several molecules from these families by quantitative RT-PCR, western blot and confocal microscopy revealed that (i) Zo-1 and Cldn18 were downregulated in all phenotypes, while Cldn4 upregulation was characteristic for neutrophilic airway inflammation; (ii) mucins Clca1 (Gob5) and Muc5ac were upregulated in eosinophilic and even more in neutrophilic asthma, and (iii) upregulation of inflammasome-related molecules such as Nlrp3, Nlrc4, Casp-1 and IL-1b was characteristic for neutrophilic asthma. Finally, we showed that inflammasome/Th-17/neutrophilic axis cytokines, namely IL-1b and IL-17 impaired epithelial barrier function and increased mucins expressions in primary human bronchial epithelial cells from normal and asthmatic donors. Our findings suggest that differential expression of TJs, mucins and inflammasome-related molecules in distinct asthma phenotypes could be mechanistically linked and might further reflect the differences observed in the clinic.

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Gene signature profiles in whole blood cells from severe asthma patinets treated with benralizumab

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