Objective: Associations have been reported between candidate genes and the response to methotrexate (MTX) in rheumatoid arthritis (RA) patients, but most of the studies have been small and have yielded conflicting results. This study was undertaken to provide a systematic review of all genetic variant associations with MTX efficacy and toxicity, and to conduct a meta-analysis evaluating the most commonly studied single-nucleotide polymorphism for which prior cumulative analysis has been lacking.
Methods: A systematic review and meta-analysis were performed to identify genetic variant associations with MTX efficacy and toxicity. Studies were identified from the Medline, EMBase, HuGENet Navigator, and Cochrane Library databases through December 2012, and from the 2009-2011 abstracts of the American College of Rheumatology and the European League Against Rheumatism annual meeting proceedings. Additional unpublished genotype data from a Canadian cohort of patients with early RA were also included.
Results: Among the 87 identified studies examining genetic associations with MTX efficacy and toxicity, the reduced folate carrier 1 gene (RFC1) variant 80G>A (Arg(27) His, rs1051266) was selected for random-effects meta-analysis. RFC1 80G>A was associated with MTX efficacy in both the recessive model (odds ratio [OR] 1.42, 95% confidence interval [95% CI] 1.04-1.93) and the additive model (OR 1.28, 95% CI 1.10-1.49). Restriction of the sensitivity analyses to studies that involved Caucasian subjects only and that used similar outcome measures (MTX failure versus nonfailure) maintained and improved the associations in both models. No significant association between RFC1 80G>A and MTX toxicity was detected.
Conclusion: In these analyses of available data from observational studies, RFC1 80G>A was found to be associated with MTX efficacy, but not toxicity, in RA patients. This variant merits further prospective analysis as a potential predictor of MTX efficacy. Variability in the definitions of response in pharmacogenetic studies is a source of data heterogeneity that should be addressed.
Copyright © 2014 by the American College of Rheumatology.