The tumor necrosis factor receptor superfamily member 1B polymorphisms predict response to anti-TNF therapy in patients with autoimmune disease: A meta-analysis

摘要

Numerous published data on the tumor necrosis factor receptor superfamily member 1B (TNFRSF1B) gene polymorphisms are shown to be associated with response or non-response to anti-TNF therapy in autoimmune diseases such as rheumatoid arthritis (RA), psoriasis and Crohn's Disease (CD). The aim of this study is to investigate whether the TNFRSF1B rs1061622 T/G or TNFRSF1A A/G rs767455 polymorphisms can predict the response to anti-TNF-based therapy in patients with autoimmune diseases. We conducted a meta-analysis of studies on the association between TNFRSF1B rs1061622 T/G polymorphism or TNFRSF1A A/G rs767455 polymorphism and non-responsiveness to anti-TNF therapy in autoimmune diseases. A total of 8 studies involving 929 subjects for TNFRSF1B rs1061622 and 564 subjects for TNFRSF1A rs767455 were finally considered. These studies consisted of seven studies on the TNFRSF1B polymorphism and four studies on the TNFRSF1A polymorphism. Meta-analysis showed significant association between the TNFRSF1B rs1061622 allele and non-responders to anti-TNF therapy [T/G odds ratio (OR) 0.72,95% confidence interval (CI) 0.57-0.93, p = 0.01]. Stratification by disease type indicated an association between the TNFRSF1B rs1061622 allele and non-responders to TNF antagonist in RA (T/G OR 0.69,95% CI 0.48-0.99,p <0.05) and psoriasis (T/G OR 0.39,95% CI 0.23-0.67, p < 0.001), but not in CD (T/G OR 1.14,95% CI 0.57-0.93, p = 0.57). And there was no association between TNFRSF1A rs767455 genotype and non-responders to the anti-TNF therapy (A/G OR 0.93,95% CI 0.70-1.23, p = 0.59). This metaanalysis demonstrates that TNFRSF1B T allele carriers show a better response to anti-TNF therapy, and individuals carrying TNFRSF1A A allele have no relationship with the response to anti-TNF therapy for autoimmune diseases. The genotyping of this polymorphism could help to optimize the treatment by identifying patients with a likely poor response to biological drugs. (C) 2015 Elsevier B.V. All rights reserved.