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Gene signatures in U-BIOPRED severe asthma for molecular phenotyping and precision medicine: time for clinical use

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TAYLOR & FRANCIS LTD
DOI: 10.1080/17476348.2023.2278606

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Severe asthma; gene signatures; differential gene expression; molecular phenotypes; endotypes; gene set variation analysis; topological data analysis

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This article introduces the use of bioinformatic approaches to analyze large omics datasets and define the inflammatory and cellular functional pathways associated with different molecular endotypes in severe asthma. Additionally, it discusses the role of mast cell activation and macrophage dysfunction in asthma.
IntroductionThe use and generation of gene signatures have been established as a method to define molecular endotypes in complex diseases such as severe asthma. Bioinformatic approaches have now been applied to large omics datasets to define the various co-existing inflammatory and cellular functional pathways driving or characterizing a particular molecular endotype.Areas coveredMolecular phenotypes and endotypes of Type 2 inflammatory pathways and also of non-Type 2 inflammatory pathways, such as IL-6 trans-signaling, IL-17 activation, and IL-22 activation, have been defined in the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes dataset. There has also been the identification of the role of mast cell activation and of macrophage dysfunction in various phenotypes of severe asthma.Expert opinionPhenotyping on the basis of clinical treatable traits is not sufficient for understanding of mechanisms driving the disease in severe asthma. It is time to consider whether certain patients with severe asthma, such as those non-responsive to current therapies, including Type 2 biologics, would be better served using an approach of molecular endotyping using gene signatures for management purposes rather than the current sole reliance on blood eosinophil counts or exhaled nitric oxide measurements.

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