Jeannette Bigler1, Michael Boedigheimer2, James P R Schofield3, Paul J Skipp3, Julie Corfield4,5, Anthony Rowe6, Ana R Sousa7, Martin Timour1, Lori Twehues2, Xuguang Hu8, Graham Roberts9, Andrew A Welcher2, Wen Yu1, Diane Lefaudeux10, Bertrand De Meulder10, Charles Auffray10, Kian F Chung11, Ian M Adcock11, Peter J Sterk12, Ratko Djukanović9. 1. 1 Amgen Inc., Seattle, Washington. 2. 2 Amgen Inc., Thousand Oaks, California. 3. 3 Centre for Biological Sciences, Southampton University, Southampton, United Kingdom. 4. 4 AstraZeneca R&D, Molndal, Sweden. 5. 5 Areteva R&D, Nottingham, United Kingdom. 6. 6 Janssen Research and Development, High Wycombe, United Kingdom. 7. 7 Respiratory Therapeutic Unit, GSK, Stockley Park, United Kingdom. 8. 8 Amgen Inc., South San Francisco, California. 9. 9 Respiratory Biomedical Research Unit, Faculty of Medicine, University Hospital Southampton, Southampton, United Kingdom. 10. 10 European Institute for Systems Biology and Medicine, Centre National de la Recherche Scientifique, Lyon, France. 11. 11 National Heart & Lung Institute, Imperial College & Biomedical Research Unit, Royal Brompton & Harefield NHS Trust, London, United Kingdom; and. 12. 12 Department of Respiratory Medicine, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands.
Abstract
RATIONALE: Stratification of asthma at the molecular level, especially using accessible biospecimens, could greatly enable patient selection for targeted therapy. OBJECTIVES: To determine the value of blood analysis to identify transcriptional differences between clinically defined asthma and nonasthma groups, identify potential patient subgroups based on gene expression, and explore biological pathways associated with identified differences. METHODS: Transcriptomic profiles were generated by microarray analysis of blood from 610 patients with asthma and control participants in the U-BIOPRED (Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes) study. Differentially expressed genes (DEGs) were identified by analysis of variance, including covariates for RNA quality, sex, and clinical site, and Ingenuity Pathway Analysis was applied. Patient subgroups based on DEGs were created by hierarchical clustering and topological data analysis. MEASUREMENTS AND MAIN RESULTS: A total of 1,693 genes were differentially expressed between patients with severe asthma and participants without asthma. The differences from participants without asthma in the nonsmoking severe asthma and mild/moderate asthma subgroups were significantly related (r = 0.76), with a larger effect size in the severe asthma group. The majority of, but not all, differences were explained by differences in circulating immune cell populations. Pathway analysis showed an increase in chemotaxis, migration, and myeloid cell trafficking in patients with severe asthma, decreased B-lymphocyte development and hematopoietic progenitor cells, and lymphoid organ hypoplasia. Cluster analysis of DEGs led to the creation of subgroups among the patients with severe asthma who differed in molecular responses to oral corticosteroids. CONCLUSIONS: Blood gene expression differences between clinically defined subgroups of patients with asthma and individuals without asthma, as well as subgroups of patients with severe asthma defined by transcript profiles, show the value of blood analysis in stratifying patients with asthma and identifying molecular pathways for further study. Clinical trial registered with www.clinicaltrials.gov (NCT01982162).
RATIONALE: Stratification of asthma at the molecular level, especially using accessible biospecimens, could greatly enable patient selection for targeted therapy. OBJECTIVES: To determine the value of blood analysis to identify transcriptional differences between clinically defined asthma and nonasthma groups, identify potential patient subgroups based on gene expression, and explore biological pathways associated with identified differences. METHODS: Transcriptomic profiles were generated by microarray analysis of blood from 610 patients with asthma and control participants in the U-BIOPRED (Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes) study. Differentially expressed genes (DEGs) were identified by analysis of variance, including covariates for RNA quality, sex, and clinical site, and Ingenuity Pathway Analysis was applied. Patient subgroups based on DEGs were created by hierarchical clustering and topological data analysis. MEASUREMENTS AND MAIN RESULTS: A total of 1,693 genes were differentially expressed between patients with severe asthma and participants without asthma. The differences from participants without asthma in the nonsmoking severe asthma and mild/moderate asthma subgroups were significantly related (r = 0.76), with a larger effect size in the severe asthma group. The majority of, but not all, differences were explained by differences in circulating immune cell populations. Pathway analysis showed an increase in chemotaxis, migration, and myeloid cell trafficking in patients with severe asthma, decreased B-lymphocyte development and hematopoietic progenitor cells, and lymphoid organ hypoplasia. Cluster analysis of DEGs led to the creation of subgroups among the patients with severe asthma who differed in molecular responses to oral corticosteroids. CONCLUSIONS: Blood gene expression differences between clinically defined subgroups of patients with asthma and individuals without asthma, as well as subgroups of patients with severe asthma defined by transcript profiles, show the value of blood analysis in stratifying patients with asthma and identifying molecular pathways for further study. Clinical trial registered with www.clinicaltrials.gov (NCT01982162).
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