Transcriptomic gene signatures associated with persistent airflow limitation in patients with severe asthma

Abstract

A proportion of severe asthma patients suffers from persistent airflow limitation (PAL), often associated with more symptoms and exacerbations. Little is known about the underlying mechanisms. Here, our aim was to discover unexplored potential mechanisms using Gene Set Variation Analysis (GSVA), a sensitive technique that can detect underlying pathways in heterogeneous samples.Severe asthma patients from the U-BIOPRED cohort with PAL (post-bronchodilator forced expiratory volume in 1 s/forced vital capacity ratio below the lower limit of normal) were compared with those without PAL. Gene expression was assessed on the total RNA of sputum cells, nasal brushings, and endobronchial brushings and biopsies. GSVA was applied to identify differentially enriched predefined gene signatures based on all available gene expression publications and data on airways disease.Differentially enriched gene signatures were identified in nasal brushings (n=1), sputum (n=9), bronchial brushings (n=1) and bronchial biopsies (n=4) that were associated with response to inhaled steroids, eosinophils, interleukin-13, interferon-α, specific CD4 T-cells and airway remodelling.PAL in severe asthma has distinguishable underlying gene networks that are associated with treatment, inflammatory pathways and airway remodelling. These findings point towards targets for the therapy of PAL in severe asthma.

Precision medicine for the discovery of treatable mechanisms in severe asthma

“…A systems biology approach would open up the way to approach this by identifying the mechanisms for treatable traits . For example, gene set variation analysis (GSVA) identified pathways that were differentially expressed in nasal brushings, sputum, bronchial brushings and bronchial biopsy samples obtained from asthmatics with airflow obstruction vs nonairflow obstruction . Differentially enriched gene signatures were associated with ICS response, eosinophils, interleukin (IL)‐13, interferon‐α, specific CD4+ T cells and airway remodelling.…”

Bronchiectasis: new therapies and new perspectives

“…Widely used examples include K-means clustering, latent class analysis and principle component analysis. 79,82,83 At the patient level, wide geographical and ethnic variation in bronchiectasis exists and may be one of the key challenges. High rates of post-infectious related disease in Asia, the enrichment for bronchiectasis in indigenous populations in the Pacific, a great NTM burden in the Americas and idiopathic disease predominating across Europe are a few examples.…”

Needs for Systems Approaches to Better Treat Individuals With Severe Asthma: Predicting Phenotypes and Responses to Treatments

“…Unfortunately, anti-IL-13 biologics were not as active as expected in severe asthmatic patients to allow further pharmaceutical development (49). It is important to bear in mind that the analysis of serum periostin and anti-IL13 biologics demonstrated that (1) the so-called type-2-immunitydriven phenotype is heterogeneous with an unequal importance of each cytokine pathway in each patient; (2) it is unlikely that a single companion biomarker can provide a specific signature for a specific endotype/phenotype/target; (3) although attractive as a serum assay, serum periostin levels have not proved to be a better discriminant of the type-2-immunity-driven phenotype than blood and sputum eosinophil counts and FeNO, especially when it comes to severe asthma (38,50); and (4) there is a need for companion markers that are able to predict the response to targeted therapies.…”