Translational Analysis of Moderate to Severe Asthma GWAS Signals Into Candidate Causal Genes and Their Functional, Tissue-Dependent and Disease-Related Associations

Effect of air pollution on asthma

Asthma is a chronic inflammatory airway disease characterized by respiratory symptoms, variable airflow obstruction, bronchial hyperresponsiveness, and airway inflammation. Exposure to air pollution has been linked to an increased risk of asthma development and exacerbation. This review aims to comprehensively summarize recent data on the impact of air pollution on asthma development and exacerbation. Specifically, we reviewed the effects of air pollution on the pathogenic pathways of asthma, including type 2 and non-type 2 inflammatory responses, and airway epithelial barrier dysfunction. Air pollution promotes the release of epithelial cytokines, driving TH2 responses, and induces oxidative stress and the production of proinflammatory cytokines. The enhanced type 2 inflammation, furthered by air pollution-induced dysfunction of the airway epithelial barrier, may be associated with the exacerbation of asthma. Disruption of the TH17/regulatory T cell balance by air pollutants is also related to asthma exacerbation. As the effects of air pollution exposure may accumulate over time, with potentially stronger impacts in the development of asthma during certain sensitive life periods, we also reviewed the effects of air pollution on asthma across the lifespan. Future research is needed to better characterize the sensitive period contributing to the development of air pollution-induced asthma and to map air pollution-associated epigenetic biomarkers contributing to the epigenetic ages onto asthma-related genes.

Effect of Obesity on the Expression of Genes Associated with Severe Asthma-A Pilot Study

Asthma is a complex condition resulting from the interaction of genes and environment. Obesity is a risk factor to develop asthma and contributes to poor response to asthma therapy and severity. The aim of the study was to evaluate the effect of obesity on the expression levels of genes previously associated with severe asthma. Three groups of subjects were studied: non-obese asthmatics (NOA), obese asthma patients (OA), and non-asthmatic obese subjects (O). Previously reported overexpressed (IL-10, MSR1, PHLDA1, SERPINB2, and CD86) and underexpressed genes (CHI3L1, CPA3, IL-8, and PI3) in severe asthma were analyzed by RT-qPCR in peripheral blood mononuclear cells (PBMCs). In the overexpressed genes, obesity significantly decreased the expression of MSR1 and PHLDA1 and had no effects on CD86, IL-10, and SERPINB2. In underexpressed genes, obesity did not affect PI3, CHI3L1, and IL-8 and significantly reduced CPA3 expression. The results of this study show that obesity should be included among the known factors that can contribute toward modifying the expression of genes associated with asthma and, in particular, severe asthma.

StarGazer: A Hybrid Intelligence Platform for Drug Target Prioritization and Digital Drug Repositioning Using Streamlit

Target prioritization is essential for drug discovery and repositioning. Applying computational methods to analyze and process multi-omics data to find new drug targets is a practical approach for achieving this. Despite an increasing number of methods for generating datasets such as genomics, phenomics, and proteomics, attempts to integrate and mine such datasets remain limited in scope. Developing hybrid intelligence solutions that combine human intelligence in the scientific domain and disease biology with the ability to mine multiple databases simultaneously may help augment drug target discovery and identify novel drug-indication associations. We believe that integrating different data sources using a singular numerical scoring system in a hybrid intelligent framework could help to bridge these different omics layers and facilitate rapid drug target prioritization for studies in drug discovery, development or repositioning. Herein, we describe our prototype of the StarGazer pipeline which combines multi-source, multi-omics data with a novel target prioritization scoring system in an interactive Python-based Streamlit dashboard. StarGazer displays target prioritization scores for genes associated with 1844 phenotypic traits, and is available via https://github.com/AstraZeneca/StarGazer.