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Effect of prednisone on type I interferon signature in rheumatoid arthritis: consequences for response prediction to rituximab
INTRODUCTION: Elevated type I interferon (IFN) response gene (IRG) expression has proven clinical relevance in predicting rituximab non-response in rheumatoid arthritis (RA). Interference between glucocorticoids (GCs) and type I IFN signaling has been demonstrated in vitro. Since GC use and dose are...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4416246/ https://www.ncbi.nlm.nih.gov/pubmed/25889713 http://dx.doi.org/10.1186/s13075-015-0564-y |
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author | de Jong, Tamarah D Vosslamber, Saskia Blits, Marjolein Wolbink, Gertjan Nurmohamed, Mike T van der Laken, Conny J Jansen, Gerrit Voskuyl, Alexandre E Verweij, Cornelis L |
author_facet | de Jong, Tamarah D Vosslamber, Saskia Blits, Marjolein Wolbink, Gertjan Nurmohamed, Mike T van der Laken, Conny J Jansen, Gerrit Voskuyl, Alexandre E Verweij, Cornelis L |
author_sort | de Jong, Tamarah D |
collection | PubMed |
description | INTRODUCTION: Elevated type I interferon (IFN) response gene (IRG) expression has proven clinical relevance in predicting rituximab non-response in rheumatoid arthritis (RA). Interference between glucocorticoids (GCs) and type I IFN signaling has been demonstrated in vitro. Since GC use and dose are highly variable among patients before rituximab treatment, the aim of this study was to determine the effect of GC use on IRG expression in relation to rituximab response prediction in RA. METHODS: In two independent cohorts of 32 and 182 biologic-free RA patients and a third cohort of 40 rituximab-starting RA patients, peripheral blood expression of selected IRGs was determined by microarray or quantitative real-time polymerase chain reaction (qPCR), and an IFN-score was calculated. The baseline IFN-score was tested for its predictive value towards rituximab response in relation to GC use using receiver operating characteristics (ROC) analysis in the rituximab cohort. Patients with a decrease in disease activity score (∆DAS28) >1.2 after 6 months of rituximab were considered responders. RESULTS: We consistently observed suppression of IFN-score in prednisone users (PREDN(+)) compared to non-users (PREDN(−)). In the rituximab cohort, analysis on PREDN(−) patients (n = 13) alone revealed improved prediction of rituximab non-response based on baseline IFN-score, with an area under the curve (AUC) of 0.975 compared to 0.848 in all patients (n = 40). Using a group-specific IFN-score cut-off for all patients and PREDN(−) patients alone, sensitivity increased from 41% to 88%, respectively, combined with 100% specificity. CONCLUSIONS: Because of prednisone-related suppression of IFN-score, higher accuracy of rituximab response prediction was achieved in PREDN(−) patients. These results suggest that the IFN-score-based rituximab response prediction model could be improved upon implementation of prednisone use. |
format | Online Article Text |
id | pubmed-4416246 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-44162462015-05-02 Effect of prednisone on type I interferon signature in rheumatoid arthritis: consequences for response prediction to rituximab de Jong, Tamarah D Vosslamber, Saskia Blits, Marjolein Wolbink, Gertjan Nurmohamed, Mike T van der Laken, Conny J Jansen, Gerrit Voskuyl, Alexandre E Verweij, Cornelis L Arthritis Res Ther Research Article INTRODUCTION: Elevated type I interferon (IFN) response gene (IRG) expression has proven clinical relevance in predicting rituximab non-response in rheumatoid arthritis (RA). Interference between glucocorticoids (GCs) and type I IFN signaling has been demonstrated in vitro. Since GC use and dose are highly variable among patients before rituximab treatment, the aim of this study was to determine the effect of GC use on IRG expression in relation to rituximab response prediction in RA. METHODS: In two independent cohorts of 32 and 182 biologic-free RA patients and a third cohort of 40 rituximab-starting RA patients, peripheral blood expression of selected IRGs was determined by microarray or quantitative real-time polymerase chain reaction (qPCR), and an IFN-score was calculated. The baseline IFN-score was tested for its predictive value towards rituximab response in relation to GC use using receiver operating characteristics (ROC) analysis in the rituximab cohort. Patients with a decrease in disease activity score (∆DAS28) >1.2 after 6 months of rituximab were considered responders. RESULTS: We consistently observed suppression of IFN-score in prednisone users (PREDN(+)) compared to non-users (PREDN(−)). In the rituximab cohort, analysis on PREDN(−) patients (n = 13) alone revealed improved prediction of rituximab non-response based on baseline IFN-score, with an area under the curve (AUC) of 0.975 compared to 0.848 in all patients (n = 40). Using a group-specific IFN-score cut-off for all patients and PREDN(−) patients alone, sensitivity increased from 41% to 88%, respectively, combined with 100% specificity. CONCLUSIONS: Because of prednisone-related suppression of IFN-score, higher accuracy of rituximab response prediction was achieved in PREDN(−) patients. These results suggest that the IFN-score-based rituximab response prediction model could be improved upon implementation of prednisone use. BioMed Central 2015-03-23 2015 /pmc/articles/PMC4416246/ /pubmed/25889713 http://dx.doi.org/10.1186/s13075-015-0564-y Text en © de Jong et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article de Jong, Tamarah D Vosslamber, Saskia Blits, Marjolein Wolbink, Gertjan Nurmohamed, Mike T van der Laken, Conny J Jansen, Gerrit Voskuyl, Alexandre E Verweij, Cornelis L Effect of prednisone on type I interferon signature in rheumatoid arthritis: consequences for response prediction to rituximab |
title | Effect of prednisone on type I interferon signature in rheumatoid arthritis: consequences for response prediction to rituximab |
title_full | Effect of prednisone on type I interferon signature in rheumatoid arthritis: consequences for response prediction to rituximab |
title_fullStr | Effect of prednisone on type I interferon signature in rheumatoid arthritis: consequences for response prediction to rituximab |
title_full_unstemmed | Effect of prednisone on type I interferon signature in rheumatoid arthritis: consequences for response prediction to rituximab |
title_short | Effect of prednisone on type I interferon signature in rheumatoid arthritis: consequences for response prediction to rituximab |
title_sort | effect of prednisone on type i interferon signature in rheumatoid arthritis: consequences for response prediction to rituximab |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4416246/ https://www.ncbi.nlm.nih.gov/pubmed/25889713 http://dx.doi.org/10.1186/s13075-015-0564-y |
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