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The association between genetic characteristics and treatment failure when switching from biologic disease-modifying antirheumatic drugs/Janus kinase inhibitors in patients with rheumatoid arthritis

https://doi.org/10.14412/1996-7012-2025-1-20-28

Abstract

Genetic polymorphisms in several genes can determine the response to therapy with biologic disease-modifying antirheumatic drugs (bDMARDs) and Janus kinase inhibitors (JAKi) in rheumatoid arthritis (RA).

Objective: to determine the association between polymorphisms of genes of IL-6 (rs1800795), IL-6R (rs2228145), TNFAIP3 (rs10499194, rs6920220), TNFα (rs1800629), CTLA-4 (rs231775), TNFSF13B (BAFF) (rs9514828), KCNS1 (rs734784), COMT (rs4633), IL-10 (rs1800872) and STAT4 (rs7574865) and inadequate response when switching RA patients from an ineffective bDMARD and/or JAKi to another bDMARD or JAKi.

Material and methods. The study group consisted of 94 patients with RA (85.1% women, mean age 47.2±13.8 years) with moderate or high disease activity that persisted despite therapy with a bDMARD/JAKi. All patients were switched to another bDMARD or JAKi, including 12 (12.8%) to a tumor necrosis factor-α inhibitor, 27 (28.7%) to an interleukin-6 inhibitor, 46 (48.9%) to rituximab and 9 (9.6%) to a JAKi. After six months, RA activity was assessed using the DAS28-CRP, SDAI and CDAI indices. Two groups of patients were identified: those who responded to treatment (n=47), achieved remission or low activity (DAS28-CRP ≤3.2, SDAI ≤11, CDAI < 10), and those who did not respond to treatment (n=47) and had moderate/high activity according to the aforementioned indices. All patients underwent genotyping of the polymorphisms of the indicated genes using the polymerase chain reaction method.

Results and discussion. Carrying the mutant T allele (TT + CT) of the TNFAIP3 polymorphism (rs10499194) and the T allele (GT + TT) of STAT4 (rs7574865) independently increased the risk of bDMARD/JAKi inefficiency (TT + CT vs. CC: odds ratio, OR 2.84; 95% confidence interval, CI 1.23–6.56; p=0.013; GT + TT vs. GG: OR 3.18; 95% CI 1.36–7.46; p=0.007). The presence of T minor alleles of TNFSF13B (BAFF) (rs9514828) and G (AG + GG) KCNS1 (rs734784) gene polymorphisms was independently associated with a lower risk of treatment failure (CC vs. CT + TT: OR 0.25; 95% CI 0.10–0.66; p=0.004; AA vs. AG + GG: OR 0.29; 95% CI 0.12–0.74; p=0.008, respectively). For the TNFA gene polymorphism (rs1800629), the multiplicative model was statistically significant (G vs. A: OR 3.12; 95% CI 1.1–9.03; p=0.037), and for the CTLA-4 gene (rs231775), the super-dominant model was statistically significant (AA + GG vs. AG: OR 2.6; 95% CI 1.14–6.25; p=0.022).

Conclusion. Six genetic predictors of treatment failure in bDMARDs/JAKi switching were identified: TNFAIP3 (rs10499194), STAT4 (rs7574865), TNFA (rs1800629), TNFSF13B (BAFF) (rs9514828), KCNS1 (rs734784) and CTLA-4 (rs231775).

About the Authors

A. O. Bobkova
V.A. Nasonova Research Institute of Rheumatology
Russian Federation

Anastasia Olegovna Bobkova,

34A, Kashirskoe Shosse, Moscow 115522



A. M. Lila
V.A. Nasonova Research Institute of Rheumatology; Russian Medical Academy of Continuing Professional Education, Ministry of Health of Russia
Russian Federation

34A, Kashirskoe Shosse, Moscow 115522;

2/1, Barrikadnaya Street, Build. 1, Moscow 125993



A. E. Karateev
V.A. Nasonova Research Institute of Rheumatology
Russian Federation

34A, Kashirskoe Shosse, Moscow 115522



I. A. Guseva
V.A. Nasonova Research Institute of Rheumatology
Russian Federation

34A, Kashirskoe Shosse, Moscow 115522



E. Yu. Samarkina
V.A. Nasonova Research Institute of Rheumatology
Russian Federation

34A, Kashirskoe Shosse, Moscow 115522



M. V. Shabatina
V.A. Nasonova Research Institute of Rheumatology
Russian Federation

34A, Kashirskoe Shosse, Moscow 115522



N. V. Konovalova
All-Russia Research Institute of Agricultural Biotechnology
Russian Federation

42, Timiryazevskaya Street, Moscow 127550



D. A. Varlamov
All-Russia Research Institute of Agricultural Biotechnology
Russian Federation

42, Timiryazevskaya Street, Moscow 127550



References

1. Nasonov EL. Prospects for rheumatoid arthritis pharmacotherapy: New opportunities and recommendations. Terapevticheskii Arkhiv. 2016; 88(12):4-10. (In Russ.).

2. Thomas K, Lazani A, Kaltsonoudis E, et al. Treatment patterns and achievement of the treat-to-target goals in a real-life rheumatoid arthritis patient cohort: data from 1317 patients. Ther Adv Musculoskelet Dis. 2020 Sep 28:12:1759720X20937132. doi: 10.1177/1759720X20937132. eCollection 2020.

3. Yu C. et al. Remission rate and predictors of remission in patients with rheumatoid arthritis under treat-to-target strategy in real-world studies: a systematic review and meta-analysis. Clin Rheumatol. 2019 Mar;38(3):727-738. doi: 10.1007/s10067-018-4340-7. Epub 2018 Oct 19.

4. Bobkova AO. Lila AM. Switching biological disease-modifying antirheumatic drugs and Janus kinase inhibitors in patients with rheumatoid arthritis. Sovremennaya Revmatologiya = Modern Rheumatology Joournal. 2023;17(3): 82-88. (In Russ.). doi; 10.14412/1996-7012-2023-3-82-88

5. Gordeev AV, Olyunin YuA, Galushko EA, et al. Difficult-to-treat rheumatoid arthritis. What is it? Sovremennaya Revmatologiya = Modern Rheumatology Joournal. 2021;15(5): 7-11. (In Russ.). doi:10.14412/1996-7012-2021-5-7-11

6. Smolen J, Aletaha D, Barton A, et al. Rheumatoid arthritis. Nat Rev Dis Primers. 2018 Feb 8:4:18001. doi: 10.1038/nrdp.2018.1

7. Kerschbaumer A, Sepriano A, Bergstra SA, et al. Efficacy of synthetic and biological DMARDs: A systematic literature review informing the 2022 update of the EULAR recommendations for the management of rheumatoid arthritis. Ann Rheum Dis. 2023 Jan;82(1):95-106. doi: 10.1136/ard-2022-223365. Epub 2022 Nov 11.

8. Smolen JS, Landewe RBM, Bergstra SA, et al. EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2022 update. Ann Rheum Dis. 2023 Jan;82(1):3-18. doi: 10.1136/ard-2022-223356. Epub 2022 Nov 10.

9. Wei K, Jiang P, Zhao J, et al. Biomarkers to Predict DMARDs Efficacy and Adverse Effect in Rheumatoid Arthritis. Front Immunol. 2022 Mar 28;13:865267. doi: 10.3389/fimmu.2022.865267.

10. Wei M, Chu CQ. Prediction of treatment response: Personalized medicine in the management of rheumatoid arthritis. Best Pract Res Clin Rheumatol. 2022 Mar;36(1):101741. doi: 10.1016/j.berh.2021.101741. Epub 2022 Jan 19.

11. Yoshii I, Sawada N, Chijiwa T. Clinical characteristics and variants that predict prognosis of difficult-to-treat rheumatoid arthritis. Rheumatol Int. 2022 Nov;42(11):1947-1954. doi: 10.1007/s00296-022-05124-1. Epub 2022 Apr 11.

12. Watanabe R, Hashimoto M, Murata K, et al. Prevalence and predictive factors of difficult-to-treat rheumatoid arthritis: the KURAMA cohort. Immunol Med. 2022 Mar; 45(1):35-44. doi: 10.1080/25785826.2021.1928383. Epub 2021 May 25.

13. Novella-Navarro M, Plasencia C, Tornero C, et al. Clinical predictors of multiple failure to biological therapy in patients with rheumatoid arthritis. Arthritis Res Ther. 2020 Dec 9;22(1): 284. doi: 10.1186/s13075-020-02354-1

14. Gamboa-Cardenas RV, Ugarte-Gil MF, Loreto M, et al. Clinical predictors of remission and low disease activity in Latin American early rheumatoid arthritis: data from the GLADAR cohort. Clin Rheumatol. 2019 Oct; 38(10):2737-2746. doi: 10.1007/s10067-019-04618-x. Epub 2019 Jun 3.

15. Avdeeva AS, Kusevich DA. The role of laboratory biomarkers in predicting the efficiency of rituximab therapy for rheumatoid arthritis: New evidence. Nauchno-prakticheskaya revmatologiya. 2017;55(3):295-303.(In Russ.).

16. Law-Wan J, Sparfel MA, Derolez S, et al. Predictors of response to TNF inhibitors in rheumatoid arthritis: An individual patient data pooled analysis of randomised controlled trials. RMD Open. 2021 Nov;7(3):e001882. doi: 10.1136/rmdopen-2021-001882.

17. Roodenrijs NMT, Welsing PMJ, van Roon J, et al. Mechanisms underlying DMARD inefficacy in difficult-to-treat rheumatoid arthritis: a narrative review with systematic literature search // Rheumatology (United Kingdom). Rheumatology (Oxford). 2022 Aug 30;61(9):3552-3566. doi: 10.1093/rheumatology/keac114.

18. Nouri B, Nair N, Barton A. Predicting treatment response to IL6R blockers in rheumatoid arthritis. Rheumatology (Oxford). 2020 Dec 1;59(12):3603-3610. doi: 10.1093/rheumatology/keaa529.

19. Ciccacci C, Conigliaro P, Perricone C, et al. Polymorphisms in STAT-4, IL-10, PSORS1C1, PTPN2 and MIR146A genes are associated differently with prognostic factors in Italian patients affected by rheumatoid arthritis. Clin Exp Immunol. 2016 Nov;186(2): 157-163. doi: 10.1111/cei.12831. Epub 2016 Aug 2.

20. Tarakji I, Habbal W, Monem F. Association Between STAT4 rs7574865 Polymorphism and Rheumatoid Arthritis: Debate Unresolved. Open Rheumatol J. 2018 Oct 24:12: 172-178. doi: 10.2174/1874312901812010172. eCollection 2018.

21. Gao W, Dong X, Yang Z, et al. Association between rs7574865 polymorphism in STAT4 gene and rheumatoid arthritis: An updated meta-analysis. Eur J Intern Med. 2020 Jan;71:101-103. doi: 10.1016/j.ejim.2019.11.009. Epub 2019 Nov 19.

22. Santillan-Lopez E, Muсoz-Valle JF, Oregon-Romero E, et al. Analysis of TNFSF13B polymorphisms and BAFF expression in rheumatoid arthritis and primary Sjögren’s syndrome patients. Mol Genet Genomic Med. 2022 Jun;10(6):e1950. doi: 10.1002/mgg3.1950. Epub 2022 Apr 12.

23. Wang YL, Li XY , Liu L, et al. Evaluation of genetic polymorphisms in TNF 308G/A rs1800629 associated with susceptibility and severity of rheumatoid arthritis: A systematic review and meta analysis. Exp Ther Med. 2024 May 13;28(1):279. doi: 10.3892/etm.2024.12567. eCollection 2024 Jul.

24. Toonen EJM, Barrera P, Fransen J, et al. Meta-analysis identified the TNFA -308G > A promoter polymorphism as a risk factor for disease severity in patients with rheumatoid arthritis. Arthritis Res Ther. 2012 Dec 7;14(6):R264. doi: 10.1186/ar4110.

25. Shen N, Ruan Y, Lu Y, et al. Three single nucleotide polymorphisms of TNFAIP3 gene increase the risk of rheumatoid arthritis. Oncotarget. 2017 Mar 28;8(13):20784-20793. doi: 10.18632/oncotarget.15265.

26. Liu W, Yang Z, Chen Y, et al. The Association Between CTLA-4, CD80/86, and CD28 Gene Polymorphisms and Rheumatoid Arthritis: An Original Study and Meta-Analysis. Front Med (Lausanne). 2021 Feb 2:8:598076. doi: 10.3389/fmed.2021.598076. eCollection 2021.

27. Zhou C, Gao S, Yuan X, et al. Association between CTLA-4 gene polymorphism and risk of rheumatoid arthritis: a meta-analysis. Aging (Albany NY). 2021 Aug 2;13(15):19397-19414. doi: 10.18632/aging.203349. Epub 2021 Aug 2.

28. Pete NM, Del Mar Maldonado Montoro M, Perez Ramirez C, et al. Impact of Single-Nucleotide Polymorphisms of CTLA-4, CD80 and CD86 on the Effectiveness of Abatacept in Patients with Rheumatoid Arthritis. J Pers Med. 2020 Nov 11;10(4):220. doi: 10.3390/jpm10040220.

29. Sainz L, Riera P, Moya P, et al. Role of IL6R Genetic Variants in Predicting Response to Tocilizumab in Patients with Rheumatoid Arthritis. Pharmaceutics. 2022 Sep 14;14(9): 1942. doi: 10.3390/pharmaceutics14091942.

30. Schotte H, Schmidt H, Gaubitz M, et al. Interleukin-6 promoter haplotypes are associated with etanercept response in patients with rheumatoid arthritis. Clin Rheumatol. 2015 Dec;34(12):2021-8. doi: 10.1007/s10067-015-3107-7. Epub 2015 Nov 3.

31. Augusto Silva dos Santos Rodrigues P, Lima de Oliveira , Mattos Brandгo K, et al. Genetic variants in the TNF pathway impact TNFi response in a mixed population with rheumatoid arthritis. Gene. 2024 Nov 30:928: 148804. doi: 10.1016/j.gene.2024.148804. Epub 2024 Jul 30.

32. Sainz L, Riera P, Moya P, et al. Impact of IL6R genetic variants on treatment efficacy and toxicity response to sarilumab in rheumatoid arthritis. Arthritis Res Ther. 2023 Nov 24; 25(1):226. doi: 10.1186/s13075-023-03209-1.

33. Janahiraman S. et al. Genetic Biomarkers as Predictors of Response to Tocilizumab in Rheumatoid Arthritis: A Systematic Review and Meta-Analysis. Genes (Basel). 2022 Jul 20;13(7):1284. doi: 10.3390/genes13071284.

34. Schotte H, Too CL, Lee KW, et al. Putative IL-10 Low Producer Genotypes Are Associated with a Favourable Etanercept Response in Patients with Rheumatoid Arthritis. PLoS One. 2015 Jun 24;10(6):e0130907. doi: 10.1371/journal.pone.0130907. eCollection 2015.

35. Robledo G, Davila-Fajardo CL, Marquez A, et al. Association between -174 interleukin-6 gene polymorphism and biological response to rituximab in several systemic autoimmune diseases. DNA Cell Biol. 2012 Sep; 31(9):1486-91. doi: 10.1089/dna.2012.1684. Epub 2012 Jun 26.

36. Zhang X, Li W, Zhang X, et al. Single nucleotide polymorphisms in TNFAIP3 were associated with the risks of rheumatoid arthritis in northern Chinese Han population. BMC Med Genet. 2014 May 15;15:56. doi: 10.1186/1471-2350-15-56.

37. Wang MJ, Yang HY, Zhang H, et al. TNFAIP3 gene rs10499194, rs13207033 polymorphisms decrease the risk of rheumatoid arthritis. Oncotarget. 2016 Dec 13;7(50): 82933-82942. doi: 10.18632/oncotarget.12638.

38. Guseva IA, Demidova NV, Soroka NE, et al. Investigation of candidate gene polymorphisms in an immune response as markers for the risk of developing rheumatoid arthritis and producing autoantibodies. Nauchno-prakticheskaya revmatologiya. 2016;54(1):21-30. (In Russ.).

39. Guseva IA. Molecular-genetic characteristics of range rheumatoid arthritis. Molekulyarnaya meditsina. 2016;14(1):15-21. (In Russ.).

40. Guseva IA, Krylov MYu, Demidova NV, et al. The RS7574865 polymorphism of the stat4 gene and risk of early rheumatoid arthritis development (The remarka study). Nauchno-Prakticheskaya Revmatologiya. 2019;57(1):62-65. (In Russ.).

41. Elshazli R, Settin A. Association of PTPN22 rs2476601 and STAT4 rs7574865 polymorphisms with rheumatoid arthritis: A meta-analysis update. Immunobiology. Immunobiology. 2015 Aug;220(8):1012-24. doi: 10.1016/j.imbio.2015.04.003. Epub 2015 Apr 28.

42. Ebrahimiyan H, Mostafaei S, Aslani S, et al. Studying the Association between STAT4 Gene Polymorphism and Susceptibility to Rheumatoid Arthritis Disease: An Updated Meta-Analysis. Iran J Immunol. 2019 Mar;16(1):71-83. doi: 10.22034/IJI.2019.39408.

43. Conigliaro P, Ciccacci C, Politi C, et al. Polymorphisms in STAT4, PTPN2, PSORS1C1 and TRAF3IP2 Genes Are Associated with the Response to TNF Inhibitors in Patients with Rheumatoid Arthritis. PLoS One. 2017 Jan 20;12(1):e0169956. doi: 10.1371/journal.pone.0169956. eCollection 2017.

44. Juge PA, Gazal S, Constantin A, et al. Variants of genes implicated in type 1 interferon pathway and B-cell activation modulate the EULAR response to rituximab at 24 weeks in rheumatoid arthritis. RMD Open. 2017 Sep 28;3(2):e000448. doi: 10.1136/rmdopen2017-000448. eCollection 2017.

45. Jiang X, Zhou Z, Zhang Y, et al. An updated meta-analysis of the signal transducer and activator of transcription 4 (STAT4) rs7574865 G/T polymorphism and rheumatoid arthritis risk in an Asian population Scand J Rheumatol. 2014;43(6):477-80. doi: 10.3109/03009742.2014.918174. Epub 2014 Sep 2.

46. Al-Sofi RF, Bergmann MS, Nielsen CH, et al. The Association between Genetics and Response to Treatment with Biologics in Patients with Psoriasis, Psoriatic Arthritis, Rheumatoid Arthritis, and Inflammatory Bowel Diseases: A Systematic Review and Meta-Analysis. Int J Mol Sci. 2024 May 26; 25(11):5793. doi: 10.3390/ijms25115793.

47. Wang Z, Kong L, Zhang H, et al. Tumor Necrosis Factor Alpha -308G/A Gene Polymorphisms Combined with Neutrophil-toLymphocyte and Platelet-to-Lymphocyte Ratio Predicts the Efficacy and Safety of AntiTNF-α Therapy in Patients with Ankylosing Spondylitis, Rheumatoid Arthritis, and Psoriasis Arthritis. Front Pharmacol. 2022 Jan 21: 12:811719. doi: 10.3389/fphar.2021.811719. eCollection 2021.

48. Maxwel 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 Nov 15;17(22): 3532-8. doi: 10.1093/hmg/ddn245. Epub 2008 Aug 19.

49. Guseva IA, Panasyuk EYu, Soroka NE, et al. Association of genetic markers with the efficiency of tocilizumab treatment for rheumatoid arthritis. Nauchno-prakticheskaya revmatologiya. 2013;51(4):377-382. (In Russ.).

50. Hernandez-Breijo B, Navarro-Compan V, Plasencia-Rodriguez C, et al. BAFF predicts immunogenicity in older patients with rheumatoid arthritis treated with TNF inhibitors. Sci Rep. 2021 Jun 2;11(1):11632. doi: 10.1038/s41598-021-91177-4.

51. Camarena DC, Marin-Rosales M, Cruz A, et al. Analysis of TNFSF13B polymorphisms and BAFF expression in rheumatoid arthritis and primary Sjögren’s syndrome patients. Mol Genet Genomic Med. 2022 Jun;10(6):e1950. doi: 10.1002/mgg3.1950. Epub 2022 Apr 12.

52. Wei F, Chang Y, Wei W. The role of BAFF in the progression of rheumatoid arthritis. Cytokine. 2015 Dec;76(2):537-544. doi: 10.1016/j.cyto.2015.07.014. Epub 2015 Jul 18.

53. Costigan M, Belfer I, Griffin RS, et al. Multiple chronic pain states are associated with a common amino acid-changing allele in KCNS1. Brain. 2010 Sep;133(9):2519-27. doi: 10.1093/brain/awq195. Epub 2010 Aug 18.

54. Chidambaran V, Gang Y, Pilipenko V, et al. Systematic Review and Meta-Analysis of Genetic Risk of Developing Chronic Postsurgical Pain. J Pain. 2020 Jan-Feb;21(1-2):2-24. doi: 10.1016/j.jpain.2019.05.008. Epub 2019 May 23.

55. Glemba KE, Guseva IA, Karateev AE, et al. Polymorphisms of the KCNS1, COMT and OPRM1 genes and development of postoperative pain in patients with osteoarthritis who underwent total knee or hip replacement. Nauchno-prakticheskaya revmatologiya. 2021; 59(5):578-583. (In Russ.).


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Bobkova AO, Lila AM, Karateev AE, Guseva IA, Samarkina EY, Shabatina MV, Konovalova NV, Varlamov DA. The association between genetic characteristics and treatment failure when switching from biologic disease-modifying antirheumatic drugs/Janus kinase inhibitors in patients with rheumatoid arthritis. Sovremennaya Revmatologiya=Modern Rheumatology Journal. 2025;19(1):20-28. https://doi.org/10.14412/1996-7012-2025-1-20-28

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ISSN 1996-7012 (Print)
ISSN 2310-158X (Online)