Evidence map›Paper›PMID 20593016›Full record

ArticlePloS one2010

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

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02878161 (Screening Protein Predictive of Response to Tumor Necrosis Factor-α Inhibitors Treatment in Chinese Rheumatoid Arthritis From "Real World" and Investigating Its Mechanism Through Signal Pathway), which is not on this map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
6.1field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT02878161 phase4unknown statusnot on this mapstarted 2016, after this paper: background citation

Screening Protein Predictive of Response to Tumor Necrosis Factor-α Inhibitors Treatment in Chinese Rheumatoid Arthritis From "Real World" and Investigating Its Mechanism Through Signal Pathway

TypeinterventionalSponsorFen LiRan2016 to 2019Enrolled240ConditionsRheumatoid ArthritisArmsmethotrexate(necessary), infliximab, etanercept, adalimumab, leflunomide (permitted, not necessary)
3 · Its place in the literature

Who cites it

42 citing papers in PubMed, 95 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 5 institutions in 2 countries.

Johan LindbergDepartment of Gene Technology, School of Biotechnology, AlbaNova University Center, Royal Institute of Technology, Stockholm, Sweden.
Carla A Wijbrandts
Lisa G van Baarsen
Gustavo Nader
Lars Klareskog
Anca Catrina
Rogier Thurlings
Margriet Vervoordeldonk
Joakim Lundeberg
Paul P Tak
Karolinska Institutet · SEUniversity of Amsterdam · NLAcademic Medical Center · NLAlbaNova · SEKTH Royal Institute of Technology · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough 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

findingsSynovial 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.

Indexed as

Gene Expression ProfilingAdultAgedAntibodies, MonoclonalAntirheumatic AgentsArthritis, RheumatoidBiopsyFemaleHumansInfliximabMaleMiddle AgedNucleic Acid HybridizationOligonucleotide Array Sequence AnalysisSynovial MembraneAntibodies, MonoclonalAntirheumatic AgentsInfliximab

Identifiers

PMID20593016
PMCPMC2892481
OpenAlexW2151954973

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.