Transcriptome analysis of controlled and therapy-resistant childhood asthma reveals distinct gene expression profiles

Background: Children with problematic severe asthma have poor disease control despite high doses of inhaled corticosteroids and additional therapy, leading to personal suffering, early deterioration of lung function, and significant consumption of health care resources. If no exacerbating factors, such as smoking or allergies, are found after extensive investigation, these children are given a diagnosis of therapy-resistant (or therapy-refractory) asthma (SA). Objective: We sought to deepen our understanding of childhood SA by analyzing gene expression and modeling the underlying regulatory transcription factor networks in peripheral blood leukocytes. Methods: Gene expression was analyzed by using Cap Analysis of Gene Expression in children with SA (n = 13), children with controlled persistent asthma (n = 15), and age-matched healthy control subjects (n = 9). Cap Analysis of Gene Expression sequencing detects the transcription start sites of known and novel mRNAs and noncoding RNAs. Results: Sample groups could be separated by hierarchical clustering on 1305 differentially expressed transcription start sites, including 816 known genes and several novel transcripts. Ten of 13 tested novel transcripts were validated by means of RT-PCR and Sanger sequencing. Expression of RAR-related orphan receptor A (RORA), which has been linked to asthma in genome-wide association studies, was significantly upregulated in patients with SA. Gene network modeling revealed decreased glucocorticoid receptor signaling and increased activity of the mitogen-activated protein kinase and Jun kinase cascades in patients with SA. Conclusion: Circulating leukocytes from children with controlled asthma and those with SA have distinct gene expression profiles, demonstrating the possible development of specific molecular biomarkers and supporting the need for novel therapeutic approaches.Peer reviewe

ARIA digital anamorphosis : Digital transformation of health and care in airway diseases from research to practice

Digital anamorphosis is used to define a distorted image of health and care that may be viewed correctly using digital tools and strategies. MASK digital anamorphosis represents the process used by MASK to develop the digital transformation of health and care in rhinitis. It strengthens the ARIA change management strategy in the prevention and management of airway disease. The MASK strategy is based on validated digital tools. Using the MASK digital tool and the CARAT online enhanced clinical framework, solutions for practical steps of digital enhancement of care are proposed.Peer reviewe

Late Breaking Abstract - Comparison of the blood transcriptomic profiles of adults and children from the U-BIOPRED asthma study

Background: We have previously reported altered gene expression in adults with asthma compared to healthy controls from the U-BIOPRED study (Bigler, 2016). Altered transcripts may define dysregulated biological pathways and identify novel therapeutic targets. We hypothesised that similar dysregulation would be seen in children with asthma. Aim: To compare blood transcriptomic profiles of children and adults with asthma. Methods: Affymetrix blood transcriptomic profiles of severe asthmatic adult non-smokers, n=152, were compared to mild moderate asthmatics, n=50 (Shaw, 2015; Fleming, 2015). Profiles of school-aged children with severe asthma, n=75, were compared to mild moderate asthmatics, n=37, and in the preschool age group severe wheeze, n=62, was compared to mild moderate wheeze, n=42. Differentially expressed genes (DEG) were identified as probe sets with maximum median group intensity >log2 5, with a significant (raw P≤0.01) change ≥ 20%. Overlapping genes were determined and pathway analysis performed. Results: We found 1887 DEG comparing severe and mild moderate asthmatic adults. Only 28 DEG were found between the severe wheeze and mild pre-school age children, with a larger signature (569 DEG) in the school aged children. 480 genes were specific to school-aged children and 1801 specific to adults, with 89 DEG in common between the adults and school-aged children. Conclusions: Preschool age children were poorly defined in terms of blood transcriptomics by the clinical definitions used. While the school-aged children showed some DEG overlap with the adults, they were distinct in many DEG and pathways indicating that childhood and adult asthma may be mechanistically different

Late Breaking Abstract - Longitudinal analysis of variation in clinical features from the U-BIOPRED severe asthma cohort

Introduction: The U-BIOPRED cohort presents an exceptional opportunity to longitudinally monitor disease variation in severe asthma.Aims: To determine the variability of severe asthma over 12-24 months in the U-BIOPRED cohort by initially focusing on clinical parameters; lung function, exacerbations and asthma symptom control.Methods: Lung function, exacerbation history and asthma control questionnaire (ACQ-5) were determined at baseline (Shaw et al.) and longitudinally.Results: 321 severe asthma patients were present in the longitudinal cohort with a mean of 454 days in the study. The longitudinal set of participants (321) were a good representation of the whole of severe asthma cohort at baseline (421). Most clinical and biomarker measurements including the FEV1 actual, exacerbation and ACQ means were not significantly different between the baseline and longitudinal visits- Table 1. There was no difference between the smoking and non-smoking cohorts. However at an individual level there was variation and some participants deteriorated, and some improved.Summary: Longitudinal U-BIOPRED data quality is valid. Further methods of analysis will move away from characterisation of group means towards understanding individual factors relating to disease progression in the U-BIOPRED cohort

Cohort Profile: Pregnancy And Childhood Epigenetics (PACE) Consortium

Epigenetics refers to mitotically heritable changes to the DNA, which do not affect the DNA sequence, but can influence its function. Currently, DNA methylation is the most studied epigenetic phenomenon in large populations. It entails the binding of a methyl group, mainly to positions in genomic DNA where a cytosine is located next to a guanine, a cytosine-phosphate-guanine (CpG) site (Figure 1). DNA methylation at CpG sites can influence gene expression by altering the DNA’s three-dimensional structure and interacting with methyl-binding proteins, consequently affecting the binding of the gene transcription and chromatin-modifying machinery. There are approximately 28 million CpG sites in the human genome. DNA methylation is a dynamic process that can be influenced by genetic factors, as well as by environmental factors such as diet, air pollution, toxicants or smoking.1–4 Hence, DNA methylation may be seen as linking the genome to the environment with respect to health and disease. Early development is a period of profound changes in DNA methylation and may, as such, be a critical period for environmentally-induced DNA methylation changes.4 Hence, this period is of specific interest for DNA methylation studies in relation to specific exposures and long-term health outcome