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Clinical Article Published

Published paper

Title: Development of SNP algorithms to predict efficacy or adverse events on infliximab or etanercept-treated patients using comprehensive gene SNP analysis.

(Japanese Clinical Rheumatology Vol.21/No.4 399-405,2009.)

 

International Conferences

1.    Authors: Matsubara T, Koyano S, Funahashi K, Toriyama S, Nakahara K, Hagiwara T, Miura T, Okuda K, Sagawa A, Sakurai T, Matsuno H, Izumihara T and Shono E: Title: An algorithm using genome-wide SNP analysis for prediction of responders and non-responders, and adverse events in tocilizumab-treated RA patients. The 73th annual meeting of the American College of Rheumatology (ACR). Philadelphia, PA, USA (2009) Purpose: Tocilizumab, a human anti-IL-6 receptor antibody, is an efficient biologic agent for inflammatory diseases such as RA. However, there is no method for prediction of responders, non-responders, and adverse events which can occur during the treatment. We established an SNP algorithm for prediction of responders or non-responders, and adverse events among tocilizumab-treated RA patients. Patients and Methods: One hundred RA patients treated with tocilizumab were included in this study. The efficacy was determined by Clinical Disease Activity Index (CDAI) within 24-30 weeks after the initial treatment. The efficacy of tocilizumab was judged by the scores of CDAI (remission and low disease activity group- 'responders', moderate and high disease activity group- 'non-responders'). Adverse events such as leukopenia, high total cholesterol, fever, and skin manifestations were documented. Genome-wide SNP genotyping was performed by Illumina HumanHap300K chip technology.  Case-control analyses between 285,548 SNPs and CDAI were examined by Fisher’s exact tests.  We selected 10 SNPs strongly associated with tocilizumab- responsiveness, or adverse events (p < 0.001). Results: Accuracy ((true positive+true negative)/total), specificity (true negative/(false positive+true negative)) and sensitivity (true positive/(true positive+false negative)) of the algorithm for responsiveness of tocilizumab ranged 92-97%. For adverse events, accuracy, specificity and sensitivity of the algorithm ranged 90-97%. It is, therefore, suggested that the SNP algorithm predict responders and adverse events prior to the initiation of treatment with this biologic agent. Conclusion: The highly accurate algorithm using SNP analysis may be useful in the prediction of responsiveness and adverse events before treatment of tocilizumab, and in this way can contribute to future tailor-made treatment with biologic agents.

2.    Authors: Matsubara T, Koyano S, Funahashi K, Toriyama S, Nakahara K, Hagiwara T, Miura T, Okuda K, Sagawa A, Sakurai T, Matsuno H, Izumihara T and Shono E: Title: Validation of an algorithm using genome-wide SNP analysis for prediction of responders and non-responders, and adverse events of infliximab or etanercept-treated RA patients by using two population samples from multiple medical cohorts. The 73th annual meeting of the American College of Rheumatology (ACR). Philadelphia, PA, USA (2009) Purpose: Infliximab (IFX) and etanercept (ETN) are efficient biologic agents for inflammatory diseases such as RA. However, there is no method for prediction of responders or non-responders, and which patients are prone to adverse events. We established and validated an SNP algorithm for prediction of responders or non-responders, and adverse events among IFX- or ETN-treated RA patients by using multiple medical cohorts. Patients and Methods: The first population samples included 187 RA patients and the second population samples included 206 patients, total 393 patients from 6 hospitals in different regions of Japan. Efficacy was determined by DAS28(CRP) within 24-30 weeks after the initial treatment with the biologics according to EULAR criteria (good and moderate response group- 'responders', poor response group- 'non-responders'), and adverse events such as fever, skin manifestations, and GI tract symptoms were documented. Genome-wide SNP genotyping was performed by HumanHap300K chip. Case-control analyses between 285,548 SNPs and efficacy or adverse events were examined by Fisher’s exact tests. We selected 10 SNPs associated with IFX- or ETN- responsiveness, or adverse events which are common in both analyses of the first and second populations (p < 0.02). Results: For IFX responsiveness, accuracy ((true positive+true negative)/total) of the algorithm of the first, second and total populations were 85.1%, 80.4% and 82.8%. For IFX adverse events, accuracy of the algorithm of the first, second and total populations were 86.3%, 88.0% and 87.3%. In responsiveness of ETN, accuracy of the algorithm of the first, second and total populations were 95.5%, 96.3% and 95.9%. The accuracy of the algorithm of ETN adverse events in the first, second and total populations were 78.3%, 88.8% and 83.4%. An endocrine hormone-acting gene was revealed in the associated genes, linking association of TNF with the endocrine hormone. Conclusion: The highly accurate algorithm using SNP analysis may prove useful in the prediction of responsiveness or determining those patients prone to adverse events before treatment of IFX or ETN, and may facilitate future tailor-made treatment of anti-TNF biologic agents.

3.    Authors: Koyano S, Funahashi K and Matsubara T: Title: Involvement of RANK and RANKL gene SNPs in joint degradation in rheumatoid arthritis. The 72th annual meeting of the American College of Rheumatology (ACR). San Francisco, CA, USA (2008) Purpose: Receptor activator of NF-kappaB (RANK) cascade system has been reported to be essential for osteoclastogenesis. Osteoclasts, activated by a variety of cytokines, are critically associated  with RA joint degradation. We examined the association of SNPs on RANK and RANKL genes in RA joint destruction. Patients and Methods: 136 RA patients were enrolled in this study.  Genotypings were performed by Illumina HumanHap 300K chip.  RA joint destruction of all patients was estimated by Steinblocker’s stage classification.  Forty eight of 136 patients were transferred to anti-TNF therapy within 5 years of onset, after at least two failed DMARD therapies.  Twenty two patients were in Steinblocker’s stage I, II (mild joint destruction) and 26 in stage III, IV (severe joint destruction) at the initiation of anti-TNF therapy.  Genotypes of SNPs on RANK and RANKL genes were extracted from HumanHap 300K chip genotyping results.  Association of these SNPs with joint destruction was examined by the case-control analysis (mild joint destruction group vs. severe group). Results: In the patient group of less than 5 years' duration, there was a marked difference in frequency in 2 SNPS on the RANK gene between the mild group and the severe group (p = 0.02-0.03).  In the patient group of more than 5 years' duration, a significant difference in frequency was observed in 2 SNPs on the RANKL gene as compared between the 2 cohorts (p = 0.01-0.02).  In all patients, the frequency of a further 5 SNPs on the RANK gene differed between the mild and severe cohorts (p = 0.01-0.05). Conclusion: The results suggested that SNPs on RANK and RANKL genes correlate with RA joint destruction and we believe that individual differences in osteoclastogenesis caused by these SNPs frequency may be responsible, at least in part, for progress of the disease.

4.    Authors: Matsubara T, Funahashi K, Toriyama S and Koyano S: Title: Algorithm using genome-wide SNP analysis for prediction of responder and non-responder, and adverse events of Infliximab or Etanercept-treated RA patients. The 72th annual meeting of the American College of Rheumatology (ACR). San Francisco, CA, USA (2008) Purpose: Infliximab and Etanercept are efficient biologic agents for inflammatory diseases such as RA. However, there are no method for prediction of responder or non-responder, and adverse events for Infliximab or Etanercept-treated patients.  Here, we examined prediction of responder or non-responder, and adverse events among Infliximab or Etanercept-treated RA patients by SNP analysis. Patients and Methods: 150 RA patients with treatment with Infliximab or Etanercept were included in this study.  The efficacy was determined by DAS28(CRP) values within 24-30 weeks after the initial treatment of the biologics according to EULAR criteria (good and moderate response group: responder, poor response group: non-responder), and adverse events such as fever, skin manifestations, and GI tract reactions were documented. Genome-wide SNP genotyping was performed by Illumina HumanHap300K chip technology.  Case-control analyses between 285,548 SNPs and clinical determination were examined by chi-square tests.  We selected 10 SNPs with strongly associated with Infliximab or Etanercept responsiveness, or their adverse events (p < 0.01).  Then, we scored relationship between each SNP and the responsiveness, estimated total score of 10 SNPs (estimated scoring in each SNP was as follows: homo allele in the majority in responder: +1 point, hetero allele: 0 point, and homo allele in the majority in non-responder: -1 point), and examined relationships between responder and non-responder, or adverse events plus or minus, and the total score. Results: Approximately 93% of the responder group has more than score 2 points, and ~95% of the non-responder group has less than score 1 point in Infliximab-responsiveness using this algorithm.  For adverse events in Inflximab-treated group, ~94% of the plus group has more than score 4 points, and ~98% of the minus group has less than score 3 points.  Similarly, for Etanercept-treated group, 90-95% of the responder, non-responder, adverse events plus or minus group could be judged by the algorithm. Conclusion: More patients are needed for more accurate prediction. Forward the future, this algorithm could be useful for prediction of responsiveness or adverse events before treatment of Infliximab or Etanercept.

5.    Authors: Matsubara T, Funahashi K, Toriyama S, Itoh H, Muramatsu M, Emi M and Koyano S: Title: Genome-wide phararmacogenomics in anti-TNF therapy of rheumatoid arthritis: Implications for their efficacy and adverse reactions. The 71th annual meeting of the American College of Rheumatology (ACR). Boston, MA, USA (2007) Purpose: Infliximab, etanercept and adalimumab have shown clinical benefit in immune-mediated inflammatory diseases such as RA. However, there remains the problem of responders and non-responders to treatment with these anti-TNF-biologics, with no method available to predict adverse events. To discover gene(s) associated with efficacy and adverse reactions, we performed an association study of RA patients by genome-wide SNP analysis. Methods: 130 RA patients with treatment with anti-TNF-biologics were included in this study. The efficacy was determined by DAS28(ESR) or DAS28(CRP) values within 24-30 weeks after the initial treatment of the biologics, and adverse reactions such as fever, skin manifestations, and GI tract reactions were documented. Genome-wide SNP genotyping was performed by Illumina HumanHap300K chip technology. After evaluations of genotyping success rate > 90% and minor allele frequency > 1%, 285,548 SNPs were eligible for the study, out of a total of 316,994 SNPs. Case-control analyses between 285,548 SNPs and clinical determination were examined by chi-square tests. Results: 150 SNPs showed strong association with efficacy (p < 0.0005), and 88 SNPs, with adverse reactions (p < 0.0005). Especially, 12 and 6 genes included at least 2 SNPs with strong association with the efficacy and adverse reactions respectively (p < 0.0005). Furthermore, the significantly associated SNPs of these genes were in strong linkage disequilibrium according to HapMap data, indicating that the SNPs consisted of certain haplotypes. These genes resided in pathways in signal transduction, cell adhesion or metabolism. Conclusion: The associated SNPs are potential candidates for predicting the efficacy or adverse reactions in anti-TNF therapy of RA. Further replication and biological studies are warranted to validate these results. Genome-wide SNP analysis could be useful for the RA-related pharmacogenomics.

6.    Authors: Matsubara T, Funahashi K, Toriyama S, Muramatsu M, Emi M and Koyano S: Title: A genome-wide SNP chip analysis revealed genes regulating the severity of rheumatoid arthritis. The 71th annual meeting of the American College of Rheumatology (ACR). Boston, MA, USA (2007) Purpose: Genome-wide association analysis using high throughput SNP typing technology has been a powerful tool for identifying disease-related genes and pharmacogenomics studies. The pathogenesis of many autoimmune diseases including RA remains unknown. To discover gene(s) regulating the severity of RA, we performed an association study of RA patients by genome-wide SNP analysis. Methods: 136 RA patients with various degrees of clinical severity were included in the study. DAS28(ESR) or DAS28(CRP) values for the RA patients before the initial treatment of the biologics including infliximab, etanercept, adalimumab or tocilizumab were used as clinical parameters (DAS28(ESR)(0 week) or DAS28(CRP)(0 week). Genome-wide SNP genotyping was performed by Illumina HumanHap300K chip technology. After evaluations of genotyping success rate > 90% and minor allele frequency > 1%, 285,548 SNPs were eligible for the study, out of a total of 316,994 SNPs. Association of 285,548 SNPs with the clinical parameter was examined by regression analysis. Results: SNPs in four genes showed strong association with both of DAS28(ESR)(0 week) and DAS(28CRP)(0week) values (p < 0.0005), and one gene was significantly associated with DAS28(CRP)(0 week) value (p < 0.0005). All of the five associated genes included at least 3 SNPs with strong association p-values (p < 0.0005). Furthermore, the significantly associated SNPs of the five genes were in strong linkage disequilibrium according to HapMap data, indicating that the SNPs consisted of certain haplotypes. The five genes resided in pathway in intracellular transport, gene transcription or metabolism. Conclusion: The associated genes are potential candidates for regulating the severity of RA. Further biological studies are warranted to investigate the mechanism by which these genes are involved in the pathogenesis of RA. Genome-wide SNP analysis could be useful for the RA-related gene search.