4.7 Article

Role of IL6R Genetic Variants in Predicting Response to Tocilizumab in Patients with Rheumatoid Arthritis

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PHARMACEUTICS
卷 14, 期 9, 页码 -

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MDPI
DOI: 10.3390/pharmaceutics14091942

关键词

IL6R; genetic variants; tocilizumab; rheumatoid arthritis; predictive factors

资金

  1. Beca STADA 2020-2021 by Societat Catalana de Reumatologia

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Rheumatoid arthritis (RA) is a common autoimmune disease, and Tocilizumab (TCZ) is a commonly used treatment. This study found that the genetic variant rs4845625 in the IL6R gene is associated with the response to TCZ treatment, which may help predict the treatment effect for patients.
Rheumatoid arthritis (RA) is a prevalent autoimmune disease characterized by chronic arthritis that may lead to irreversible joint damage and significant disability. Patients with RA are commonly treated with Tocilizumab (TCZ), an IL-6 receptor (IL-6R) antagonist, but many patients refractorily respond to this therapy. Identifying genetic biomarkers as predictors of TCZ response could be a key to providing a personalized medicine strategy. We aimed to evaluate whether functional single nucleotide polymorphisms (SNPs) in the IL6R gene could predict TCZ response in patients with RA. We retrospectively included 88 RA patients treated with TCZ. Six SNPs previously described in the IL6R gene (rs12083537, rs11265618, rs4329505, rs2228145, rs4537545, and rs4845625) were genotyped in DNA samples from these patients. Using parametric tests, we evaluated the association between these polymorphisms and clinicopathological features. Responses to treatments were assessed at six months using three variables: a quantitative improvement in Disease activity score including 28 joints (DAS28), a satisfactory European League Against Rheumatism (EULAR) response, and low disease activity (LDA) achievement. The three response variables studied were associated with genetic variant rs4845625, and no association was found with the other five SNPs. Our findings support the potential clinical value of SNPs in the IL6R gene as predictive biomarkers for TCZ response.

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