Further resolution of non-T2 asthma subtypes from high-throughput sputum transciptomics data in U-BIOPRED
Author(s)
Type
Conference Paper
Abstract
Background: Precision medicine of asthma requires understanding of its heterogeneity and molecular pathophysiology.
Aim: Three sputum-derived transcriptomic clusters (TACs) were previously identified [Kuo at al. Eur Respir J.2017, 49] in the U-BIOPRED cohort: TAC1 consisting of T2 high patients with eosinophilia, TAC2 with neutrophilia and inflammasome activation and TAC3, a more heterogeneous cluster with mostly paucigranulocytic patients. We further refine TAC3.
Methods: Gaussian mixture modelling for model-based clustering was applied to sputum gene expression of 104 asthmatic participants from the adult cohort to substructure TAC3. Gene set variation analysis (GSVA) was used to explore the enrichment of gene signatures across the TACs.
Results: We again produce the three TACs (TAC1 N=23, TAC2 N=24) but TAC3 was further split into two groups (TAC3a N=28, TAC3b N=29), distinguished by distinct neutrophils and macrophages density and enrichment of IL13 stimulation, inflammasome activation and OXPHOS gene signatures (Figure), as well as IL-4 and LPS-stimulated macrophage gene signatures. However, there were no distinguishing clinical features.
Conclusion: Identification of sub-structure of sputum TACs, particularly of TAC3, will help towards improved targeted therapies.
Aim: Three sputum-derived transcriptomic clusters (TACs) were previously identified [Kuo at al. Eur Respir J.2017, 49] in the U-BIOPRED cohort: TAC1 consisting of T2 high patients with eosinophilia, TAC2 with neutrophilia and inflammasome activation and TAC3, a more heterogeneous cluster with mostly paucigranulocytic patients. We further refine TAC3.
Methods: Gaussian mixture modelling for model-based clustering was applied to sputum gene expression of 104 asthmatic participants from the adult cohort to substructure TAC3. Gene set variation analysis (GSVA) was used to explore the enrichment of gene signatures across the TACs.
Results: We again produce the three TACs (TAC1 N=23, TAC2 N=24) but TAC3 was further split into two groups (TAC3a N=28, TAC3b N=29), distinguished by distinct neutrophils and macrophages density and enrichment of IL13 stimulation, inflammasome activation and OXPHOS gene signatures (Figure), as well as IL-4 and LPS-stimulated macrophage gene signatures. However, there were no distinguishing clinical features.
Conclusion: Identification of sub-structure of sputum TACs, particularly of TAC3, will help towards improved targeted therapies.
Date Issued
2018-11-19
Date Acceptance
2018-11-01
Citation
European Respiratory Journal, 2018, 52, pp.1-3
ISSN
0903-1936
Publisher
European Respiratory Society
Start Page
1
End Page
3
Journal / Book Title
European Respiratory Journal
Volume
52
Copyright Statement
© 2018 The authors.
Sponsor
Commission of the European Communities
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000455567107302&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
115010
Source
28th International Congress of the European-Respiratory-Society (ERS)
Subjects
Science & Technology
Life Sciences & Biomedicine
Respiratory System
Publication Status
Published
Start Date
2018-09-15
Finish Date
2018-09-19
Coverage Spatial
Paris, FRANCE
Date Publish Online
2018-11-19