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Member Research & Reports

Member Research & Reports

Taiwan: Researchers Apply Bioinformatical Methods to Identify Asthma Clusters with Neutrophil-predominant Phenotype

According to a collaborative study by National Taiwan University and National Taiwan University Hospital, researchers found that different childhood asthma phenotypes evoke various clinical symptoms and vary in their responses to treatment. Dr. Yungling Lee, professor, and colleagues established phenotypic clusters of childhood asthma using 12 clinical parameters. This study enrolled asthmatic children diagnosed by a pediatric asthma specialist under the Global Initiative for Asthma (GINA) guideline. The research team applied the k-means algorithm and clustered 351 participants into five distinct asthma clusters. In the gene expression profiles analysis, significant differences were noted for samples in cluster 2, which contained children with the highest percentage of neutrophils, the highest BMI, and a higher exacerbation rate. Cluster 2 (neutrophil-predominant asthma) was characterized as a severe asthma phenotype in children and demonstrated a unique gene expression profile, in comparison with other asthma phenotypes. To reveal the role of neutrophil in corticosteroid response of asthma, the research team established an independent corticosteroid response cohort. Elevated levels of serum neutrophil elastase and IL-8 was also noted to be associated with poor corticosteroid responsiveness in asthma.

The conception and design of the study was from Dr. Lee, associate professor at National Taiwan University College of Public Health of  and dedicated to genetic epidemiology and molecular epidemiology.

Dr.  Lee is the corresponding author and the leader of Taiwanese Consortium of Childhood Asthma Study (TCCAS). “The study applied a novel bioinformatical method to classify asthmatic patients into five clusters with distinct inflammatory profiles. Neutrophil-predominant asthma is the most severe asthma phenotype with poor corticosteroid response. Gene expression profile of different asthma phenotypes not only improve our knowledge of childhood asthma, but can also guide asthma precision medicine.” said Prof. Lee.

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