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ABSTRACT: For prevention of joint destruction in rheumatoid arthritis, optimal management of therapy with disease-modifying antirheumatic drugs is essential. Pharmacogenomic evidence, if reliable, may be incorporated in the treatment of rheumatoid arthritis to achieve a more efficient activity control with minimized adverse events.
We conducted retrospective studies to validate our previous three different results about the association between adverse events or efficacy of two different disease-modifying antirheumatic drugs and genomic variations. Association between single nucleotide polymorphisms in N-acetyltransferase 2 gene (NAT2) and adverse events by sulfasalazine and association between C677T or A1298C in 5,10-methylenetetrahydrofolate reductase gene (MTHFR) and responses to methotrexate were examined.
Patients without the wild-type haplotype at NAT2 were more likely to suffer from overall adverse events [n=186, P=0.001, relative risk (RR) 3.31, 95% confidence interval (CI) 1.76-6.22] and severe adverse events (P=0.015, RR 24.6, 95% CI 2.37-254.53) by sulfasalazine. Patients with the T allele at C677T in MTHFR were more susceptible to overall adverse events (n=156, P=0.003; RR 2.4, 95% CI 1.29-4.55) while patients with the C allele at A1298C were less likely to be treated with a higher dose (>6 mg/week) of methotrexate in one year of treatment (n=159, P=0.008, RR 1.84, 95% CI 1.12-3.01). In all three association studies, the results were essentially the same as previously reported.
As three studies on the associations between genomic variations and adverse events or efficacy of two different disease-modifying antirheumatic drugs were replicated, the usefulness of the tests is worth being tested in clinical practice.
Pharmacogenetics and Genomics 06/2007; 17(6):383-90. · 3.48 Impact Factor
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ABSTRACT: The use of haplotype information in case-control studies is an area of focus for the research on the association between phenotypes and genetic polymorphisms. We examined the validity of the application of the likelihood-based algorithm, which was originally developed to analyze the data from cohort studies or clinical trials, to the data from case-control studies. This algorithm was implemented in a computer program called PENHAPLO. In this program, haplotype frequencies and penetrances are estimated using the expectation-maximization algorithm, and the haplotype-phenotype association is tested using the generalized likelihood ratio. We show that this algorithm was useful not only for cohort studies but also for case-control studies. Simulations under the null hypothesis (no association between haplotypes and phenotypes) have shown that the type I error rates were accurately estimated. The simulations under alternative hypotheses showed that PENHAPLO is a robust method for the analysis of the data from case-control studies even when the haplotypes were not in HWE, although real penetrances cannot be estimated. The power of PENHAPLO was higher than that of other methods using the likelihood-ratio test for the comparison of haplotype frequencies. Results of the analysis of real data indicated that a significant association between haplotypes in the SAA1 gene and AA-amyloidosis phenotype was observed in patients with rheumatoid arthritis, thereby suggesting the validity of the application of PENHAPLO for case-control data.
Genetics 12/2006; 174(3):1505-16. · 4.01 Impact Factor
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ABSTRACT: Bayesian inference has been used for genetic risk calculation. In this traditional method, inheritance events are divided into a number of cases under the inheritance model, and some elements of the inheritance model are usually disregarded. We developed a genetic risk calculation program, GRISK, which contains an improved Bayesian risk calculation algorithm to express the outcome of inheritance events with inheritance vectors, a set of ordered genotypes of founders, and mutation vectors, which represent a new idea for description of mutations in a pedigree. GRISK can calculate genetic risk in a common format that allows users to execute the same operation in every case, whereas the traditional risk calculation method requires construction of a calculation table in which the inheritance events are variously divided in each respective case. In addition, GRISK does not disregard any possible events in inheritance. This program was developed as a Japanese macro for Excel to run on Windows.
Journal of Human Genetics 01/2006; 51(4):387-90. · 2.57 Impact Factor
