Association of the 5-aminoimidazole-4-carboxamide ribonucleotide transformylase gene with response to methotrexate in juvenile idiopathic arthritis. Issue 8 (22nd April 2011) - Hinks, Anne; Moncrieffe, Halima; Martin, Paul; Ursu, Simona; Lal, Sham; Kassoumeri, Laura; Weiler, Tracey; Glass, David N; Thompson, Susan D; Wedderburn, Lucy R; Thomson, Wendy
Abstract : Objectives: Methotrexate (MTX) is the mainstay treatment for juvenile idiopathic arthritis (JIA), however approximately 30% of children will fail to respond to the drug. Identification of genetic predictors of response to MTX would be invaluable in developing optimal treatment strategies for JIA. Using a candidate gene approach, single nucleotide polymorphisms (SNPs) within genes in the metabolic pathway of MTX, were investigated for association with response to treatment in JIA cases. Methods: Tagging SNPs were selected across 13 MTX metabolic pathway genes and were genotyped using Sequenom genotyping technology in subjects recruited from the Sparks Childhood Arthritis Response to Medication Study. Response to MTX was defined using the American College of Rheumatology (ACR) paediatric response criteria and SNP genotype frequencies were compared between the worst and best responders (ACR-Ped70) to MTX. An independent cohort of US JIA cases was available for validation of initial findings. Results: One SNP within the inosine triphosphate pyrophosphatase gene ( ITPA ) and two SNPs within 5-aminoimidazole-4-carboxamide ribonucleotide transformylase gene ( ATIC ) were significantly associated with a poor response to MTX. One of the ATIC SNPs showed a trend towards association with MTX response in an independent cohort of US JIA cases. Meta-analysis of the two studies strengthened this association (combined p value=0.002). Conclusions: This study presents association of a SNP in the ATIC gene with response to MTX in JIA. There is now growing evidence to support a role of the ATIC gene with response to MTX treatment. These results could contribute towards a better understanding of and ability to predict MTX response in JIA.