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Predictive genetic biomarkers for the efficacy of methotrexate in rheumatoid arthritis: a systematic review

The Pharmacogenomics Journal volume 20, pages 159–168 (2020)Cite this article

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Abstract

Multiple pharmacogenetic studies investigated the effectiveness of methotrexate. However, due to the use of nonvalidated outcomes, lack of validation or conflicting results it remains unclear if genetic markers can help to predict response to MTX treatment. Therefore, a systematic review was performed. PubMed was searched for articles reporting potential pharmacogenetic biomarkers associated (p < 0.05) with MTX efficacy using the validated endpoints DAS(28), EULAR, or ACR response criteria. The PICO method was used for study selection, and PRISMA guidelines to prepare the report. Thirty-five studies met the inclusion criteria, providing 39 potential genetic biomarkers in 19 genes. After Bonferroni correction, six genetic biomarkers were associated with the efficacy of MTX: ATIC rs7563206; SLC19A1 rs1051266; DHFR rs836788; TYMS rs2244500, rs2847153, and rs3786362 in at least one study. Only SLC19A1 rs1051266 was replicated in an independent cohort and promising for predicting methotrexate efficacy.

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Acknowledgements

We are particularly grateful for the assistance for search terms given by Jan Schoones of the Walaeus library (LUMC).

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Authors and Affiliations

  1. Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands

    Frank Eektimmerman, Jesse J. Swen, Moenira B. Madhar & Henk-Jan Guchelaar

  2. Leiden Network for Personalised Therapeutics https://www.lumc.nl/org/lnpt/

    Frank Eektimmerman, Jesse J. Swen & Henk-Jan Guchelaar

  3. Department of Rheumatology, Leiden University Medical Center, Leiden, The Netherlands

    Cornelia F. Allaart

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  1. Frank Eektimmerman
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Correspondence to Henk-Jan Guchelaar.

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Eektimmerman, F., Swen, J.J., Madhar, M.B. et al. Predictive genetic biomarkers for the efficacy of methotrexate in rheumatoid arthritis: a systematic review. Pharmacogenomics J 20, 159–168 (2020). https://doi.org/10.1038/s41397-019-0098-9

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