Rachael Tan and Anne Barton
ARC Epidemiology Unit, Stopford Building, The University of Manchester, Manchester, UK
Correspondence: Anne Barton,
Arthritis Research Campaign Epidemiology Unit, University of Manchester, M13 9PT, UK
E-mail: anne.barton@manchester.ac.uk
Key words: genetics, rheumatoid arthritis, response, etanercept, infliximab, adalimumab.
Conflict of interest: the authors reported no potential conflict of interests.
©Copyright R. Tan and A. Barton, 2009
Licensee PAGEPress, Italy
Rheumatology Reports 2009; 1:e1
doi:10.4081/rr.2009.e1
AbstractThe introduction of anti-tumor necrosis factor (anti-TNF) agents has dramatically improved the outlook for many patients with rheumatoid arthritis (RA). However, 30% of patients fail to respond to treatment for unknown reasons. While research has identified clinical markers of response, including baseline disease activity, disability and the concurrent use of disease modifying therapy, these account for only a small proportion of the variation in treatment response. A number of groups, therefore, have started to investigate genetic markers of response to anti-TNF therapies. To date, many of these studies have been small, underpowered and have largely been restricted to the analysis of candidate genes. The only replicated and validated genetic predictor of anti-TNF response is the 308G>A SNP in the TNF promoter region, but the amount of variation in response accounted for by this marker is modest. It is unknown whether variation in treatment response is determined by several genes each with a small effect size or small numbers of genes with large effect sizes but what is certain is the need for a non-hypothesis driven approach in order to identify further genetic markers of anti-TNF response. The identification of genetic predictors of response to anti-TNF therapies would enable clinicians to tailor treatment of these expensive and potentially harmful agents to patients most likely to benefit from them. |
The introduction of anti-tumor necrosis factor (TNF) drugs revolutionized the treatment of rheumatoid arthritis (RA) particularly for patients who showed little or no response to disease modifying anti-rheumatic drugs (DMARDs). There are currently three anti-TNF drugs licensed for treatment of RA in the UK. They are etanercept (Enbrel®), adalimumab (Humira®) and infliximab (Remicade®). Etanercept is a fusion protein of two p75 TNF receptors that are linked to the Fc component of the human immunoglobulin Ig-G1. It works by binding to soluble TNF and neutralizing it but can also bind lymphotoxin-a (LTA). Adalimumab and infliximab are monoclonal antibodies directed against membrane-bound and soluble TNFa.1 Whilst DMARDs may slow radiological progression, studies using anti-TNF drugs have shown their superiority in suppressing structural change.2 However, anti-TNFs are not without their drawbacks. As well as being expensive, studies have shown links with malignancy and serious infections.3 Furthermore, for unknown reasons, up to 30% of patients fail to respond to treatment with anti-TNFs.4 In many countries, these concerns limit the wholesale use of these drugs. In the UK, for example, the National Institute for Health and Clinical Excellence (NICE) advises that anti-TNF therapies can be prescribed for RA patients who:
• have a 28-joint count disease activity score (DAS28) of >5.1 on 2 occasions;
• have previously tried two DMARDs which have failed, one being methotrexate.5
These guidelines were developed based on the cost-benefit analysis but may mean that patients destined to require anti-TNF therapy experience undue delays in receiving treatment, with the consequent burden of sustained disease activity. If it were possible to identify those patients most, or indeed least, likely to respond to treatment, the altered cost-benefit ratio may allow better targeting of these expensive treatments.
There are currently few clinical or biological predictors of response to anti-TNF drugs. Hyrich et al. conducted a large study investigating clinical predictors of response in patients receiving either etanercept or infliximab.6 Patients were recruited from the British Society for Rheumatology (BSR) Biologics Register, an observational cohort study which aims to recruit and follow up 4,000 patients on each of the 3 currently licensed anti-TNF drugs. The study concluded that current use of NSAIDs and methotrexate improved response while poorer response was achieved in smokers and those with higher baseline disability scores.6 Subsequently, Kristensen et al. confirmed that concomitant treatment with methotrexate improved response to anti-TNF therapies. They also concluded that gender was not a predictor of response, but disease activity and poor functional ability at baseline were.7 However, these clinical factors only explained a minority of the variation in response to therapy.
With the disappointing results from studies investigating clinical factors, research is moving towards identifying other markers that may predict response to anti-TNF therapy. Positivity for either rheumatoid factor or anti-CCP antibody tests have been reported to be associated with a poorer response to therapy but, even combined with clinical predictors, only 17% in the variation of treatment response was explained in one study.8
A number of investigators have hypothesized that genetic variation may affect response to anti-TNF therapies. Support for this theory comes from studies of response to other drugs in which genetic variation has been shown to play an important role. For example, up to 50% of the variation in warfarin dose required between individuals can be explained by single nucleotide polymorphisms (SNPs) within 2 genes, cytochrome P450 C29 (CYP2C9) and VKORC1.9
A number of genetic studies have been undertaken using different study designs. In designing studies to investigate genetic predictors of response to anti-TNF therapies, there has been debate as to whether studies should investigate the anti-TNF agents individually or as a class. Evidence that infliximab is effective in Crohn’s disease while etanercept and adalimumab are not fuels the argument that the different anti-TNFs work via different pathways.10,11 Similarly, patients who have failed to respond to one anti-TNF drug may benefit from a second supporting the idea that response to each of the anti-TNF drugs should be analyzed separately. However, a large study showed that the reason for stopping the second anti-TNF was often the same as for the first, reinforcing the argument that anti-TNFs work in a similar manner and, therefore, that there may be a class effect in treatment response.12 Table 1 lists the studies in which response to anti-TNF drugs has been analyzed as a class effect for a number of candidate genes.
Many authors, however, have analyzed response to the anti-TNF drugs separately, as outlined in Tables 2-4, in order to reduce heterogeneity in the patient population. It should be noted that only one study to date has investigated polymorphisms associated with response to adalimumab therapy alone (Table 4). This most likely reflects the fact that this drug was the one most recently licensed and, therefore, there will be fewer patients receiving this therapy at the current time.
These studies raise a number of points for discussion. Firstly, the sample sizes included to date are small in comparison with those tested when investigating susceptibility genes. Plenge et al. highlighted in a recent review that to detect a SNP with an odds ratio (OR) of 3 (equivalent to the effect of the shared epitope) recruitment of several hundred participants would be required.33 Therefore, investigation of SNPs with much smaller OR may require studies with thousands of participants to give statistical power to the results. It is not clear at the moment whether a small number of genes with large effect sizes or a large number of genes with small effect sizes will determine response to these therapies but, even so, the majority of reported studies have been underpowered to detect even large effects making it difficult to interpret statistically insignificant results. Where positive associations have been reported, there are few examples where the findings have been subsequently validated in independent cohorts. One notable exception is the TNF-308G>A SNP (rs1800629), association with which has been replicated in independent studies and been shown to be a weak predictor of anti-TNF treatment response. Previous functional studies have suggested that patients carrying -308 A allele express higher levels of TNF.24, 26, 27
Secondly, the response criteria vary between the different studies conducted. Some studies have used American College of Rheumatology (ACR) response criteria while others have used DAS 28 (Tables 1-4). 13, 20, 21, 23 Although previous work has validated the sensitivity and specificity of these measures, they are somewhat subjective and potentially open to manipulation. For example, it has been shown that the DAS28 is greatly influenced by the tender joint count, which is a very subjective measure.34 Hence, it may be argued that more objective measures of response, such as the percentage improvement in the erythrocyte sedimentation rate (ESR) or C- reactive protein (CRP) may be more robust.
Thirdly, the different studies have taken different approaches when trying to account for baseline co-variables. Smoking, baseline DAS28, age, concurrent DMARD therapy and disability [as measured by the health assessment questionnaire (HAQ)] influence absolute change in DAS28 but not all studies have adjusted for these potential confounders. This leads to difficulties when trying to conduct a meta-analysis incorporating all available data.
Finally, all of these pharmacogenetic studies have investigated SNPs that map to obvious RA candidate genes such as the TNFa gene. However, as has been demonstrated by genome wide association (GWA) studies of RA susceptibility, associated variants often map to loci that had not previously been identified as important in the pathogenesis of RA.35 This highlights the need for a hypothesis-free approach to pharmacogenetics. At the moment, the availability of large, well-phenotyped cohorts of anti-TNF treated patients and suitable resources for undertaking GWA studies limit progress in this field. However, initiatives to bring together researchers in order to pool resources and samples are underway. Such national and international collaboration will be necessary to advance this clinically important research. Ultimately, the identification of predictors of response, whether they are genetic or otherwise, has the potential to make an enormous impact on clinical practice by helping physicians to target the right therapies to the right patients.
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Table 1. Studies investigating association between genes and response to combinations of anti-TNFs. The table below summarises the studies to date investigating genes and response to anti-TNF therapies in which the studies did not separate the three anti-TNF drugs but investigated a class effect of treatment response. |
 |
Table 2. Studies investigating predictors of etanercept response. |
 |
Table 3. Studies investigating predictors of response to infliximab. |
 |
Table 4. Study investigating predictors of response to adalimumab. |
1. Ranganathan P. Pharmacogenomics of tumor necrosis factor antagonists in rheumatoid arthritis. Pharmacogenomics 2005;6:481-90.[PubMed]
2. Lipsky PE, van der Heijde DM, St Clair EW, et al. Infliximab and methotrexate in the treatment of rheumatoid arthritis. Anti-Tumor Necrosis Factor Trial in Rheumatoid Arthritis with Concomitant Therapy Study Group. N Engl J Med 2000; 343:1594-602.[PubMed]
3. Bongartz T, Sutton AJ, Sweeting MJ, et al. Anti-TNF antibody therapy in rheumatoid arthritis and the risk of serious infections and malignancies: systematic review and meta-analysis of rare harmful effects in randomized controlled trials.[see comment][erratum appears in JAMA. 2006; 295:2482]. JAMA 2006;295:2275-85.[PubMed]
4. Coenen MJ, Toonen EJ, Scheffer H, et al. Pharmacogenetics of anti-TNF treatment in patients with rheumatoid arthritis. Pharmacogenomics 2007;8:761-73.[PubMed]
5. National Institute for Health and Clinical Excellence. Adalimumab, etanercept and infliximab for the treatment of rheumatoid arthritis. http://www.nice.org uk/Guidance/ TA130 2007 October. Available from: URL: http://www.nice.org.uk/Guidance/TA130
6. Hyrich KL, Watson KD, Silman AJ, Symmons DPM. Predictors of response to anti-TNF-alpha therapy among patients with rheumatoid arthritis: results from the British Society for Rheumatology Biologics Register. Rheumatology 2006;45: 1558-65.[PubMed]
7. Kristensen LE, Kapetanovic MC, Gulfe A, et al. Predictors of response to anti-TNF therapy according to ACR and EULAR criteria in patients with established RA: results from the South Swedish Arthritis Treatment Group Register. Rheumatology 2008;47:495-9.[PubMed]
8. Potter C, Hyrich KL, Tracey A, et al. Association of rheumatoid factor and anti-cyclic citrullinated peptide positivity, but not carriage of shared epitope or PTPN22 susceptibility variants, with anti-tumour necrosis factor response in rheumatoid arthritis. Ann Rheum Dis 2009;68:69-74.[PubMed]
9. Bodin L, Verstuyft C, Tregouet DA, et al. Cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase (VKORC1) genotypes as determinants of acenocoumarol sensitivity. Blood 2005;106:135-40.[PubMed]
10. Sandborn WJ, Hanauer SB, Katz S, et al. Etanercept for active Crohn's disease: a randomized, double-blind, placebo-controlled trial. Gastroenterology 2001;121: 1088-94.[PubMed]
11. Kooloos WM, de Jong DJ, Huizinga TW, Guchelaar HJ. Potential role of pharmacogenetics in anti-TNF treatment of rheumatoid arthritis and Crohn's disease. Drug Discov Today 2007;12:125-31.[PubMed]
12. Hyrich KL, Lunt M, Watson KD, et al. Outcomes after switching from one anti-tumor necrosis factor alpha agent to a second anti-tumor necrosis factor alpha agent in patients with rheumatoid arthritis: Results from a Large UK National Cohort Study. Arthritis Rheum 2007;56:13-20. [PubMed]
13. Toonen EJ, Coenen MJ, Kievit W, et al. The tumour necrosis factor receptor superfamily member 1b 676T>G polymorphism in relation to response to infliximab and adalimumab treatment and disease severity in rheumatoid arthritis. Ann Rheum Dis 2008;67:1174-7.[PubMed]
14. Seitz M, Wirthmuller U, Moller B, Villiger PM. The -308 tumour necrosis factor-alpha gene polymorphism predicts therapeutic response to TNFalpha-blockers in rheumatoid arthritis and spondyloarthritis patients. Rheumatology (Oxford) 2007;46: 93-6.[PubMed]
15. Fabris M, Di PE, Sacco S, et al. [TNF- alpha gene polymorphisms in rheumatoid arthritis patients treated with anti-TNF-alpha agents: preliminary results]. Reumatismo 2002;54:19-26.[PubMed]
16. Tutuncu Z, Kavanaugh A, Zvaifler N, et al. Fcgamma receptor type IIIA polymorphisms influence treatment outcomes in patients with inflammatory arthritis treated with tumor necrosis factor alpha-blocking agents. Arthritis Rheum 2005;52:2693-6.[PubMed]
17. Kastbom A, Bratt J, Ernestam S, et al. Fcgamma receptor type IIIA genotype and response to tumor necrosis factor alpha-blocking agents in patients with rheumatoid arthritis. Arthritis Rheum 2007;56: 448-52.[PubMed]
18. Padyukov L, Lampa J, Heimburger M, et al. Genetic markers for the efficacy of tumour necrosis factor blocking therapy in rheumatoid arthritis. Ann Rheum Dis 2003;62:526-9.[PubMed]
19. Kang CP, Lee KW, Yoo DH, et al. The influence of a polymorphism at position -857 of the tumour necrosis factor alpha gene on clinical response to etanercept therapy in rheumatoid arthritis. Rheumatology (Oxford) 2005;44:547-52.[PubMed]
20. Schotte H, Schluter B, Drynda S, et al. Interleukin 10 promoter microsatellite polymorphisms are associated with response to long term treatment with etanercept in patients with rheumatoid arthritis. Ann Rheum Dis 2005;64:575-81.[PubMed]
21. Guis S, Balandraud N, Bouvenot J, et al. Influence of -308 A/G polymorphism in the tumor necrosis factor alpha gene on etanercept treatment in rheumatoid arthritis. Arthritis Rheum 2007;57:1426-30.[PubMed]
22. Criswell LA, Lum RF, Turner KN, et al. The influence of genetic variation in the HLA-DRB1 and LTA-TNF regions on the response to treatment of early rheumatoid arthritis with methotrexate or etanercept. Arthritis Rheum 2004;50:2750-6.[PubMed]
23. Maxwell JR, Potter C, Hyrich KL, et al. Association of the tumour necrosis factor-308 variant with differential response to anti-TNF agents in the treatment of rheumatoid arthritis. Hum Mol Genet 2008;17:3532-8.[PubMed]
24. Mugnier B, Balandraud N, Darque A, et al. Polymorphism at position -308 of the tumor necrosis factor alpha gene influences outcome of infliximab therapy in rheumatoid arthritis. Arthritis Rheum 2003;48:1849-52.[PubMed]
25. Martinez A, Salido M, Bonilla G, et al. Association of the major histocompatibility complex with response to infliximab therapy in rheumatoid arthritis patients. Arthritis Rheum 2004;50:1077-82.[PubMed]
26. Cuchacovich M, Ferreira L, Aliste M, et al. Tumour necrosis factor-alpha (TNF-alpha) levels and influence of -308 TNF-alpha promoter polymorphism on the responsiveness to infliximab in patients with rheumatoid arthritis. Scand J Rheumatol 2004;33:228-32.[PubMed]
27. Balog A, Klausz G, Gal J, Molnar T, et al. Investigation of the prognostic value of TNF-alpha gene polymorphism among patients treated with infliximab, and the effects of infliximab therapy on TNF-alpha production and apoptosis. Pathobiology 2004;71:274-80.[PubMed]
28. Marotte H, Arnaud B, Diasparra J, et al. Association between the level of circulating bioactive tumor necrosis factor alpha and the tumor necrosis factor alpha gene polymorphism at -308 in patients with rheumatoid arthritis treated with a tumor necrosis factor alpha inhibitor. Arthritis Rheum 2008;58:1258-63.[PubMed]
29. Fonseca JE, Carvalho T, Cruz M, et al. Polymorphism at position -308 of the tumour necrosis factor alpha gene and rheumatoid arthritis pharmacogenetics. Ann Rheum Dis 2005;64:793-4.[PubMed]
30. Tolusso B, Pietrapertosa D, Morelli A, et al. IL-1B and IL-1RN gene polymorphisms in rheumatoid arthritis: relationship with protein plasma levels and response to therapy. Pharmacogenomics 2006;7:683-95.[PubMed]
31. Chatzikyriakidou A, Georgiou I, Voulgari PV, et al. Combined tumour necrosis factor-alpha and tumour necrosis factor receptor genotypes could predict rheumatoid arthritis patients' response to anti-TNF-alpha therapy and explain controversies of studies based on a single polymorphism. Rheumatology (Oxford) 2007;46: 1034-5.[PubMed]
32. Cuchacovich M, Soto L, Edwardes M, et al. Tumour necrosis factor (TNF)alpha -308 G/G promoter polymorphism and TNFalpha levels correlate with a better response to adalimumab in patients with rheumatoid arthritis. Scand J Rheumatol 2006;35:435-40.[PubMed]
33. Plenge RM, Criswell LA. Genetic variants that predict response to anti-tumor necrosis factor therapy in rheumatoid arthritis: current challenges and future directions. Curr Opin Rheumatol 2008;20:145-52.[PubMed]
34. Harth M, Pope J. The measure of our measures. Rheumatology (Oxford) 2004; 43:1465-7.[PubMed]
35. Barton A, Thomson W, Ke X, et al. Rheumatoid arthritis susceptibility loci at chromosomes 10p15, 12q13 and 22q13. Nat Genet 2008;40:1156-9.[PubMed]
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