The gene expression profile in the synovium as a predictor of the clinical response to infliximab treatment in rheumatoid arthritis

Johan Lindberg, Carla A. Wijbrandts, Lisa G. van Baarsen, Gustavo Nader, Lars Klareskog, Anca Catrina, Rogier Thurlings, Margriet Vervoordeldonk, Joakim Lundeberg, Paul P. Tak

Research output: Contribution to journalArticle

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Abstract

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 whole 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.

Original languageEnglish (US)
Article numbere11310
JournalPloS one
Volume5
Issue number6
DOIs
StatePublished - Aug 12 2010

Fingerprint

rheumatoid arthritis
Synovial Membrane
Transcriptome
Gene expression
Rheumatoid Arthritis
cell aggregates
gene expression
Lymphocytes
Tissue
lymphocytes
Therapeutics
Genes
Biopsy
Biomarkers
Microarrays
Metabolism
Oligonucleotides
Medicine
Infliximab
arthroscopy

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

Cite this

Lindberg, Johan ; Wijbrandts, Carla A. ; van Baarsen, Lisa G. ; Nader, Gustavo ; Klareskog, Lars ; Catrina, Anca ; Thurlings, Rogier ; Vervoordeldonk, Margriet ; Lundeberg, Joakim ; Tak, Paul P. / The gene expression profile in the synovium as a predictor of the clinical response to infliximab treatment in rheumatoid arthritis. In: PloS one. 2010 ; Vol. 5, No. 6.
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abstract = "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 whole 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.",
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Lindberg, J, Wijbrandts, CA, van Baarsen, LG, Nader, G, Klareskog, L, Catrina, A, Thurlings, R, Vervoordeldonk, M, Lundeberg, J & Tak, PP 2010, 'The gene expression profile in the synovium as a predictor of the clinical response to infliximab treatment in rheumatoid arthritis', PloS one, vol. 5, no. 6, e11310. https://doi.org/10.1371/journal.pone.0011310

The gene expression profile in the synovium as a predictor of the clinical response to infliximab treatment in rheumatoid arthritis. / Lindberg, Johan; Wijbrandts, Carla A.; van Baarsen, Lisa G.; Nader, Gustavo; Klareskog, Lars; Catrina, Anca; Thurlings, Rogier; Vervoordeldonk, Margriet; Lundeberg, Joakim; Tak, Paul P.

In: PloS one, Vol. 5, No. 6, e11310, 12.08.2010.

Research output: Contribution to journalArticle

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T1 - The gene expression profile in the synovium as a predictor of the clinical response to infliximab treatment in rheumatoid arthritis

AU - Lindberg, Johan

AU - Wijbrandts, Carla A.

AU - van Baarsen, Lisa G.

AU - Nader, Gustavo

AU - Klareskog, Lars

AU - Catrina, Anca

AU - Thurlings, Rogier

AU - Vervoordeldonk, Margriet

AU - Lundeberg, Joakim

AU - Tak, Paul P.

PY - 2010/8/12

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N2 - 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 whole 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.

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