Arthritis & Rheumatism, Volume 62,
November 2010 Abstract Supplement
Abstracts of the American College of
Rheumatology/Association of Rheumatology Health Professionals
Annual Scientific Meeting
Atlanta, Georgia November 6-11, 2010.
Candidate Gene Analysis in US Veteran Rheumatoid Arthritis Patients with Clinical Improvement during Treatment with Anti-Tumor Necrosis Factor Agents in the Veterans Affairs Rheumatoid Arthritis (VARA) Registry.
Cannon5, Grant W., Wolff5, Roger K., Ying8, Jian, Hayden6, Candace L., Sauer6, Brian C., Curtis7, Jeffrey R., Johnson3, Dannette S.
Dallas VA and University of Texas Southwestern
Washington DC VA and Georgetown University
Denver VA and University of Colorado
Jackson VA and University of Mississippi
Omaha VA and University of Nebraska
Salt Lake City VA and University of Utah, Salt Lake City, UT
Salt Lake City VA and University of Utah
University of Alabama
University of Utah
Washington DC VA and Georgetown and Howard Universities
While anti-tumor necrosis factor (anti-TNF) agents are effective in rheumatoid arthritis (RA) patients, these benefits are not universal. Several genes are associated with either RA susceptibility or severity. In RA patients being treated with adalimumab, etanercept, or infliximab, multiple SNPs of known RA susceptibility genes were measured and correlated with 28 joint count disease activity scores (DAS28).
Effectiveness of anti-TNF therapy in RA patients enrolled in the Veterans Affairs RA (VARA) registry was defined by two methods. In method #1, patients receiving >=90 days of anti-TNF in the VA pharmacy benefits management database were compared. Clinical effectiveness required an average DAS28 <=3.2 during the observation period from 90 days after initiation of anti-TNF treatment until the end of the anti-TNF course. In method #2, VARA patients initiating an anti-TNF and sustaining a DAS28 <=3.2 after one year (±2 months) while on continued treatment with the same anti-TNF were defined as having clinical effectiveness. In addition, these patients evaluated by method #2 could not have initiated or escalated corticosteroid therapy, initiated a traditional disease modifying antirheumatic drug, or had more than one joint injection to be classified as having clinical effectiveness.
Caucasian men VARA patients were genotyped for polymorphisms within CTLA4 (5 SNPs), PADI1 (15 SNPs), PTPN22 (5 SNPs), STAT4 (26 SNPs), TRAF1-C5 (17 SNPs), IL10 (4 SNPs), TNF-alpha (3 SNPs) and shared epitope (SE). Using SAS, logistic regression was performed to test the effects of genotypes on the response to the treatment. We assessed significance with a Bonferroni correction (Pcutoff=0.0005)
Method #1 classified 106 (34%) of 307 eligible patients and method #2 classified 73 (36%) of 201 as having an effective clinical response. With method #1, the increase of each copy of SE was associated with an increase of 67.8% (15.8%, 143.1%) in odds of response to anti-TNF. Comparing to null, compound heterozygous SE is significantly (p=0.005) associated with a higher odds of response ((OR 3.1, 95% CI (1.4, 6.7)). The odds of response for homozygous and heterozygous SE were 51.1% and 42.5% higher respectively, but did not reach statistical significance. No association of SE with clinical response was seen with SE by method #2. Neither method demonstrated a significant association with clinical response for the other candidate gene SNPs. Given the small sample size, the power to detect genetic effect is not high, we only have a power of 35% to detect of a 2-fold effect a SNP given the minor allele frequency (MAF) of the SNP is as high as 0.2, and the power would be even lower when either the genetic effect or the MAF is smaller.
This analysis suggests that SE genotype may be associated with anti-TNF effectiveness but failed to demonstrate any statically significant difference in other RA susceptibility gene polymorphism in US veterans with and without clinical effectiveness during anti-TNF therapy. The different results with these two methods emphasize the importance of phenotype definition in these genetic analyses.
To cite this abstract, please use the following information:
Cannon, Grant W., Wolff, Roger K., Ying, Jian, Hayden, Candace L., Sauer, Brian C., Curtis, Jeffrey R., et al; Candidate Gene Analysis in US Veteran Rheumatoid Arthritis Patients with Clinical Improvement during Treatment with Anti-Tumor Necrosis Factor Agents in the Veterans Affairs Rheumatoid Arthritis (VARA) Registry. [abstract]. Arthritis Rheum 2010;62 Suppl 10 :1099