OBJECTIVE: Among patients with rheumatoid arthritis (RA), there is a high degree of interindividual variability in the degree of response to methotrexate (MTX) treatment. This study was undertaken to explore polymorphisms in genes contributing to antiinflammatory adenosine release as novel predictors of MTX treatment outcome. METHODS: In 205 patients with newly diagnosed RA, 5 polymorphisms in 5 genes coding for enzymes related to the release of adenosine were analyzed. All patients received standardized MTX treatment (up to 25 mg per week orally), combined with folic acid. MTX efficacy was evaluated by the Disease Activity Score (DAS) and compared among genotypes. The association between MTX-related adverse events and genotype was also assessed. The following polymorphisms were determined: AMPD1 34C>T, ATIC 347C>G, ITPA 94C>A, MTR 2756A>G, and MTRR 66A>G. When significant differences were found by chi-square analysis, odds ratios (ORs) and 95% confidence intervals were calculated. RESULTS: Patients carrying the AMPD1 34T allele, ATIC 347CC, or ITPA 94CC were more likely to have a good clinical response, as defined by a DAS of < or =2.4 (OR [95% confidence interval] 2.1 [1.0-4.5], 2.5 [1.3-4.7], and 2.7 [1.1-8.1], respectively). The likelihood of a good clinical response was increased if patients possessed all 3 favorable genotypes (OR 27.8 [95% confidence interval 3.2-250]). Regarding toxicity, only ATIC G allele carriers experienced a greater frequency of adverse events (OR 2.0 [95% confidence interval 1.1-3.7]). CONCLUSION: Polymorphisms in the AMPD1, ATIC, and ITPA genes are associated with good clinical response to MTX treatment. These findings indicate that genotyping may help in the identification of patients who will benefit most from MTX treatment and may assist clinicians in making treatment decisions regarding patients with recent-onset RA.
RCT Entities:
OBJECTIVE: Among patients with rheumatoid arthritis (RA), there is a high degree of interindividual variability in the degree of response to methotrexate (MTX) treatment. This study was undertaken to explore polymorphisms in genes contributing to antiinflammatory adenosine release as novel predictors of MTX treatment outcome. METHODS: In 205 patients with newly diagnosed RA, 5 polymorphisms in 5 genes coding for enzymes related to the release of adenosine were analyzed. All patients received standardized MTX treatment (up to 25 mg per week orally), combined with folic acid. MTX efficacy was evaluated by the Disease Activity Score (DAS) and compared among genotypes. The association between MTX-related adverse events and genotype was also assessed. The following polymorphisms were determined: AMPD1 34C>T, ATIC 347C>G, ITPA 94C>A, MTR 2756A>G, and MTRR 66A>G. When significant differences were found by chi-square analysis, odds ratios (ORs) and 95% confidence intervals were calculated. RESULTS:Patients carrying the AMPD1 34T allele, ATIC 347CC, or ITPA 94CC were more likely to have a good clinical response, as defined by a DAS of < or =2.4 (OR [95% confidence interval] 2.1 [1.0-4.5], 2.5 [1.3-4.7], and 2.7 [1.1-8.1], respectively). The likelihood of a good clinical response was increased if patients possessed all 3 favorable genotypes (OR 27.8 [95% confidence interval 3.2-250]). Regarding toxicity, only ATIC G allele carriers experienced a greater frequency of adverse events (OR 2.0 [95% confidence interval 1.1-3.7]). CONCLUSION: Polymorphisms in the AMPD1, ATIC, and ITPA genes are associated with good clinical response to MTX treatment. These findings indicate that genotyping may help in the identification of patients who will benefit most from MTX treatment and may assist clinicians in making treatment decisions regarding patients with recent-onset RA.
Authors: Torben S Mikkelsen; Caroline F Thorn; Jun J Yang; Cornelia M Ulrich; Deborah French; Gianluigi Zaza; Henry M Dunnenberger; Sharon Marsh; Howard L McLeod; Kathy Giacomini; Mara L Becker; Roger Gaedigk; James Steven Leeder; Leo Kager; Mary V Relling; William Evans; Teri E Klein; Russ B Altman Journal: Pharmacogenet Genomics Date: 2011-10 Impact factor: 2.089
Authors: R B Warren; R L Smith; E Campalani; S Eyre; C H Smith; J N W N Barker; J Worthington; C E M Griffiths Journal: Br J Dermatol Date: 2008-10-25 Impact factor: 9.302