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OP0236 Whole Transcriptome Investigation of Response To Anti-TNF Treatment in Rheumatoid Arthritis


Background Despite the revolutionary impact of anti-TNF treatments on rheumatoid arthritis (RA) patients, good disease control is only achieved in 30% of patients. In current clinical practice, RA drugs are administered on a trial and error basis and there are no clinical biomarkers of response to guide treatment decisions. Whilst non-responding patients can be switched to alternative therapies at 3 months, many remain on ineffective therapy for longer periods. Identification of early predictors of response could support timely switching in patients whose disease activity is not controlled by a particular drug.

Objectives To investigate gene expression levels in whole-blood collected from patients with RA, between the start of treatment (baseline) and following 3-months of treatment, to identify a biological biomarker of response to the anti-TNF drug adalimumab.

Methods EULAR good responders (GR) and non-responders (NR) to adalimumab were selected from the Biologics in RA Genetics and Genomics Study Syndicate (BRAGGSS) cohort. Total RNA was isolated from Tempus™-stabilised baseline and 3-month blood samples using the MagMAX™ RNA Isolation Kit and quality assessed using the Agilent Bioanalyzer 2100. Samples with an RNA integrity number >4 were amplified and converted into biotinylated sense-strand DNA using the Affymetrix WT PLUS Kit and hybridised to Affymetrix GeneChip® Human Transcriptome Arrays. Quality control and differential transcription analysis was performed using the Affymetrix Expression and Transcriptome Analysis Console™.

Results Whole genome expression profiling was performed on 44 patient samples (31 GR and 12 NR to adalimumab treatment). Gene level paired-analysis of variance revealed the significant downregulation of 1776 transcripts and upregulation of 943 transcripts following 3 months of adalimumab treatment in GR (FDR p-value <0.05, fold change >1.2 or < -1.2) (Figure). There were no significant differences in gene expression between baseline and 3 months in NR. Pathway analysis using the Database for Annotation, Visualization and Integrated Discovery (DAVID) revealed that both differentially expressed and differentially spliced genetic variants in GR were heavily enriched for relevant processes including antigen processing and presentation, ribosome biogenesis and T- and B-cell receptor signalling. Many of the most significantly upregulated genes encoded immunoglobulin and MHC II components, which may indicate immune cell migration from the synovium into the blood in a positive response to adalimumab therapy in GR.

Conclusions A blood-based biomarker for good-response to anti-TNF treatment at 3 months could allow prompt identification of non-response, reducing the impact of long-term radiological damage and facilitating more responsible pharmacological spending. To support the promising immune signature of good-response at 3 months identified herein, subsequent work will include replication in additional patients and integration with corresponding genotype and serum microRNA data.

Disclosure of Interest None declared

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