https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:20353 Wed 11 Apr 2018 10:11:19 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:14184 1% predicted of 76%, and 69% were taking inhaled corticosteroids. Thirteen healthy controls without asthma were also assessed. Inflammatory cell counts were performed, and RNA was extracted from selected sputum. Transcriptional profiles were generated (Illumina Humanref-8 V2) and analyzed by using GeneSpring GX11. Results: Unsupervised hierarchical clustering of gene expression profiles in asthma revealed 3 distinct groups. The first transcriptional phenotype (n = 21) had lower FEV₁% predicted and higher asthma control questionnaire scores, exhaled nitric oxide, and sputum eosinophils. The second transcriptional phenotype (n = 14) had lower FEV₁% predicted and forced vital capacity % predicted and higher sputum neutrophils compared with a third transcriptional phenotype (n = 24) that had higher sputum macrophages and resembled healthy controls. Differentially expressed genes between transcriptional asthma phenotypes were related to inflammatory and immune responses. Genes in the IL-1 and TNF-α/nuclear factor-κB pathways were overexpressed and correlated with clinical parameters and neutrophilic airway inflammation. Conclusion: Gene expression profiling provides a novel means to investigate the molecular mechanisms and classifications of asthma phenotypes. There are 3 distinct transcriptional phenotypes of asthma that relate to both clinical and inflammatory parameters.]]> Sat 24 Mar 2018 08:21:53 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:47870 Fri 03 Feb 2023 14:42:59 AEDT ]]>