Literature DB >> 24321457

A single nucleotide polymorphism of TRAF1 predicts the clinical response to anti-TNF treatment in Japanese patients with rheumatoid arthritis.

T Nishimoto1, N Seta, R Anan, T Yamamoto, Y Kaneko, T Takeuchi, M Kuwana.   

Abstract

OBJECTIVES: Recent genome-wide association studies disclosed that several single nucleotide polymorphisms (SNPs), including tumour necrosis factor (TNF) receptor-associated factor 1 (TRAF1) (+16860A/G), are associated with the pathophysiology of rheumatoid arthritis (RA). We assessed the usefulness of TRAF1 genotyping as a genetic predictor of the response to anti-TNF treatment in Japanese RA patients.
METHODS: TRAF1 (+16860A/G) was genotyped using the TaqMan SNP genotyping assay in 101 Japanese RA patients treated with anti-TNF drugs for >24 weeks. We retrospectively analysed the association between SNP and the clinical response to treatment. TRAF1 mRNA and protein expression was also evaluated in CD4+, CD8+, CD14+, or CD19+ cells from 25 healthy subjects using quantitative polymerase chain reaction and intracellular staining flow cytometry, respectively.
RESULTS: No statistical difference in DAS28-ESR at baseline was observed between the patient groups with the AA, AG, or GG genotype. The GG genotype was more frequent in non-responders than in good or moderate responders [odds ratio (OR) 7.4, 95% confidence interval (CI) 1.5-37.5]. The non-responders possessed the G allele more frequently than the good or moderate responders (OR 3.5, 95% CI 1.4-9.0). TRAF1 protein expression increased significantly in CD14+ monocytes from healthy subjects with the GG genotype compared with that in subjects with the AA or AG genotype.
CONCLUSIONS: TRAF1 (+16860A/G) may be useful for predicting the clinical response to anti-TNF treatment and may contribute to resistance to treatment in RA patients with the GG genotype by increasing the TRAF1 expression in circulating inflammatory cells.

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Year:  2013        PMID: 24321457

Source DB:  PubMed          Journal:  Clin Exp Rheumatol        ISSN: 0392-856X            Impact factor:   4.473


  10 in total

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9.  Gene Ontology Analysis Highlights Biological Processes Influencing Non-Response to Anti-TNF Therapy in Rheumatoid Arthritis.

Authors:  Gregor Jezernik; Mario Gorenjak; Uroš Potočnik
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10.  A longitudinal genome-wide association study of anti-tumor necrosis factor response among Japanese patients with rheumatoid arthritis.

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  10 in total

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