T-helper cell type 2 (Th2) and non-Th2 molecular phenotypes of asthma using sputum transcriptomics in U-BIOPRED

Abstract

Asthma is characterised by heterogeneous clinical phenotypes. Our objective was to determine molecular phenotypes of asthma by analysing sputum cell transcriptomics from 104 moderate-to-severe asthmatic subjects and 16 nonasthmatic subjects.After filtering on the differentially expressed genes between eosinophil- and noneosinophil-associated sputum inflammation, we used unbiased hierarchical clustering on 508 differentially expressed genes and gene set variation analysis of specific gene sets.We defined three transcriptome-associated clusters (TACs): TAC1 (characterised by immune receptors , and ), TAC2 (characterised by interferon-, tumour necrosis factor-α- and inflammasome-associated genes) and TAC3 (characterised by genes of metabolic pathways, ubiquitination and mitochondrial function). TAC1 showed the highest enrichment of gene signatures for interleukin-13/T-helper cell type 2 (Th2) and innate lymphoid cell type 2. TAC1 had the highest sputum eosinophilia and exhaled nitric oxide fraction, and was restricted to severe asthma with oral corticosteroid dependency, frequent exacerbations and severe airflow obstruction. TAC2 showed the highest sputum neutrophilia, serum C-reactive protein levels and prevalence of eczema. TAC3 had normal to moderately high sputum eosinophils and better preserved forced expiratory volume in 1 s. Gene-protein coexpression networks from TAC1 and TAC2 extended this molecular classification.We defined one Th2-high eosinophilic phenotype TAC1, and two non-Th2 phenotypes TAC2 and TAC3, characterised by inflammasome-associated and metabolic/mitochondrial pathways, respectively.

Personalised medicine: are we ready?

“…Eosinophilic asthma shows molecular upregulation of so-called T-helper cell type 2 (Th2) pathways, while upregulation of local innate immunity was found to be prominent in neutrophilic asthma [18]. The U-BIOPRED study, which used a sophisticated unbiased statistical approach and in-depth molecular and gene analysis of sputum from cohorts of moderate to severe asthma patients, has confirmed the heterogeneity of molecular pathways in different clinical and physiological phenotypes of asthma [19].…”

From systems biology to P4 medicine: applications in respiratory medicine

“…By doing so, they are paving the way for a radical shift in medical practice that is evolving from a reactive proposition to a predictive, preventive, personalised and participatory (P4) approach. Respiratory medicine is in fact already contributing significantly to this change by leading the field of data-driven management [98,99] as well as by applying multilevel network analysis to a variety of clinical conditions [127].…”

“…1) ADEPT (Airways Disease Endotyping for Personalised Therapeutics) and U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcome Consortium) have, for instance, applied a clustering algorithm to two independent asthma cohorts on a small set of easily measurable clinical variables and successfully defined four longitudinally stable clusters of patients with distinct clinical and biomarker profiles (from blood, sputum and airway data) [98]. 2) KUO et al [99] recently reported three novel molecular phenotypes of asthma in the U-BIOPRED cohort by analysing sputum cell transcriptomics in asthmatic and nonasthmatic subjects. They applied hierarchical clustering of differentially expressed genes as well as gene set variation analysis, gene-protein coexpression and pathway enrichment analysis.…”

Severe asthma: phenotyping to endotyping or vice versa?

“…KUO et al [19], authors of a paper published in this issue of the European Respiratory Journal, have examined subjects recruited with the entry criteria for Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED), a pan-European public-private collaboration funded by the European Commission's Innovative Medicines Initiative [10,18]. Although the authors have already reported clinical and pathological clustering analyses [15], and found four phenotypes not much different from those previously reported [20,21], they reasoned that clustering severe asthma using clinical features may not only not provide a precise definition of severe asthma, but may even preclude the collection of adequate information on the underlying mechanisms of each phenotype.…”

“…Thus, KUO et al [19] tried a new approach to the study of possible endotypes, exploring the driving mechanisms of the various inflammatory profiles by clustering differentially expressed genes in the sputum cells of eosinophilic versus noneosinophilic moderate-to-severe asthmatics from the U-BIOPRED cohort. With this approach they were able to define three transcriptome-associated clusters (TACs): TAC 1, an interleukin (IL)-13/T-helper (Th)2-high predominantly eosinophilic cluster; and TAC 2 and TAC 3, both non-Th2 phenotypes characterised by association with interferon (IFN)/tumour necrosis factor-α (TNF-α)/inflammasome (TAC 2) and metabolic and mitochondrial pathways (TAC 3).…”