Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Distinct, non-overlapping gene panels of peripheral blood gene expression predict response to infliximab therapy in rheumatoid arthritis and Crohn's disease

ABSTRACT: We used microarrays to identify markers predicting responder status in infliximab treatment in 19 rheumatoid arthritis and 20 Crohn's disease patients at week 0 and week 2 of treatment. Peripheral blood samples were obtained at week 0 and week 2 of inxliximab treatment and global gene expression profiling identified markers of responder status.

ORGANISM(S): Homo sapiens

SUBMITTER: Bertalan Mesko

PROVIDER: E-GEOD-42296 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Background: Although the use of TNF inhibitors has fundamentally changed the way rheumatoid arthritis (RA) is treated, not all patients respond well. It is desirable to facilitate the identification of responding and non-responding patients prior to treatment, not only to avoid unnecessary treatment but also for financial reasons. In this work we have investigated the transcriptional profile of synovial tissue sampled from RA patients before anti-TNF treatment with the aim to identify biomarkers predictive of response. Methodology/Principal Findings: Synovial tissue samples were obtained by arthroscopy from 62 RA patients before the initiation of infliximab treatment. RNA was extracted and gene expression profiling was performed using an in-house spotted long oligonucleotide array covering 17972 unique genes. Tissue sections were also analyzed by immunohistochemistry to evaluate cell infiltrates. Response to infliximab treatment was assessed according to the EULAR response criteria. The presence of lymphocyte aggregates dominated the expression profiles and a significant overrepresentation of lymphocyte aggregates in good responding patients confounded the analyses. A statistical model was set up to control for the effect of aggregates, but no differences could be identified between responders and non-responders. Subsequently, the patients were split into lymphocyte aggregate positive- and negative patients. No statistically significant differences could be identified except for 38 transcripts associated with differences between good- and non-responders in aggregate positive patients. A profile was identified in these genes that indicated a higher level of metabolism in good responding patients, which indirectly can be connected to increased inflammation. Conclusions/Significance: It is pivotal to account for the presence of lymphoid aggregates when studying gene expression patterns in rheumatoid synovial tissue. In spite of our original hypothesis, the data do not support the notion that microarray analysis of synovial biopsy specimens can be used in the context of personalized medicine to identify non-responders to anti-TNF therapy before the initiation of treatment. All patients were hybridized in a dual channel reference design where the reference was always labeled with cy3 and the samples with cy5. In total, RNA was extracted from synovial biopsies of 62 patients. 18 patients were good responding, 30 moderate responding and 14 non-responding. Universal Human Reference RNA from Stratagene was used as reference. All samples were amplified with the RiboAmp II kit before labeling and hybridization.

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Distinct, non-overlapping gene panels of peripheral blood gene expression predict response to infliximab therapy in rheumatoid arthritis and Crohn's disease

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