Molecular discrimination of responders and non-responders to anti-TNF-alpha therapy in rheumatoid arthritis by etanercept

Dirk Koczan , Susanne Drynda , Michael Hecker , Andreas Drynda , Reinhard Guthke , Joern Kekow and Hans-Juergen Thiesen

Arthritis Research & Therapy 2008, 10:R50doi:10.1186/ar2419


Published:	2 May 2008

Abstract (provisional)

Introduction

About thirty percent of rheumatoid arthritis (RA) patients fail to respond adequately to TNFa blocking therapy. There is a medical and socioeconomic need to identify molecular markers for an early prediction of responders and non-responders.

Methods

Hereto, RNA was extracted from PBMC of 19 RA patients before first application of the TNFa blocker etanercept as well as after 72. Clinical response was assessed over 3 months using the 28 joint count Disease Activity Score (DAS28) and X-rays. Supervised learning methods were applied to Affymetrix Human Genome U133 microarray data analysis to determine highly selective discriminatory gene pairs or triplets with prognostic relevance for the clinical outcome evinced by a decline of DAS28 by 1.2.

Results

Early down-regulation of expression levels secondary to TNFa neutralization was associated with good clinical responses as shown by a decline in overall disease activity 3 months after start of treatment. Informative gene sets include genes (e.g. NFKBIA, CCL4, IL8, IL1B, TNFAIP3, PDE4B, PPP1R15A and ADM) involved in different pathways and cellular processes such as TNFa signalling via NFkB, NFkB independent signalling via cAMP, and the regulation of cellular and oxidative stress response. Pairs and triplets within these genes were found to have a high prognostic value reflected by prediction accuracies of over 89% for 7 selected gene pairs and 95% for 10 specific gene triplets.

Conclusions

Our data underline that early gene expression profiling is instrumental in identifying candidate biomarkers to predict therapeutic outcomes of anti-TNFa treatment regimes.