BACKGROUND: Rheumatoid arthritis (RA) is a genetically complex disease where the response to different treatments varies greatly between different patients. This is the case with the tumour necrosis factor (TNF) blocking agents, where 20-40% of patients have been described as non-responders. No predictive markers exist as yet for the prognosis of response. OBJECTIVE: To analyse whether polymorphisms of several cytokine genes are associated with the responsiveness to TNF blockade with etanercept. METHODS: 123 patients with active RA were treated with etanercept and response rates were determined after three months using American College of Rheumatology (ACR)20 and disease activity score (DAS)28 response criteria. Genotyping was done for TNF (-308 TNFA), interleukin (IL)10 (-1087 IL10), transforming growth factor (TGF)beta1 (codon 25 TGFB1), and IL1 receptor antagonist (intron 2 IL1RN). RESULTS: 24 patients (20%) were defined as non-responders owing to their failure to fulfil any of the ACR20 or DAS28 response criteria. None of the recorded alleles was alone significantly associated with responsiveness to treatment. However, a certain combination of alleles (-308 TNF1/TNF1 and -1087 G/G) was associated with good responsiveness to etanercept (p<0.05). In addition, a combination of alleles influencing interleukin 1 receptor antagonist (IL1Ra) and TGFbeta1 production (A2 allele for IL1RN and rare C allele in codon 25 of TGFB1 gene) was associated with non-responsiveness (p<0.05). CONCLUSION: Genetic polymorphisms, which may influence the balance of pro- and anti-inflammatory cytokines of relevance for the course of RA, are associated with clinical responsiveness to etanercept treatment.
BACKGROUND:Rheumatoid arthritis (RA) is a genetically complex disease where the response to different treatments varies greatly between different patients. This is the case with the tumour necrosis factor (TNF) blocking agents, where 20-40% of patients have been described as non-responders. No predictive markers exist as yet for the prognosis of response. OBJECTIVE: To analyse whether polymorphisms of several cytokine genes are associated with the responsiveness to TNF blockade with etanercept. METHODS: 123 patients with active RA were treated with etanercept and response rates were determined after three months using American College of Rheumatology (ACR)20 and disease activity score (DAS)28 response criteria. Genotyping was done for TNF (-308 TNFA), interleukin (IL)10 (-1087 IL10), transforming growth factor (TGF)beta1 (codon 25 TGFB1), and IL1 receptor antagonist (intron 2 IL1RN). RESULTS: 24 patients (20%) were defined as non-responders owing to their failure to fulfil any of the ACR20 or DAS28 response criteria. None of the recorded alleles was alone significantly associated with responsiveness to treatment. However, a certain combination of alleles (-308 TNF1/TNF1 and -1087 G/G) was associated with good responsiveness to etanercept (p<0.05). In addition, a combination of alleles influencing interleukin 1 receptor antagonist (IL1Ra) and TGFbeta1 production (A2 allele for IL1RN and rare C allele in codon 25 of TGFB1 gene) was associated with non-responsiveness (p<0.05). CONCLUSION: Genetic polymorphisms, which may influence the balance of pro- and anti-inflammatory cytokines of relevance for the course of RA, are associated with clinical responsiveness to etanercept treatment.
Authors: R Maini; E W St Clair; F Breedveld; D Furst; J Kalden; M Weisman; J Smolen; P Emery; G Harriman; M Feldmann; P Lipsky Journal: Lancet Date: 1999-12-04 Impact factor: 79.321
Authors: D Sankaran; A Asderakis; S Ashraf; I S Roberts; C D Short; P A Dyer; P J Sinnott; I V Hutchinson Journal: Kidney Int Date: 1999-07 Impact factor: 10.612
Authors: D T Felson; J J Anderson; M Boers; C Bombardier; D Furst; C Goldsmith; L M Katz; R Lightfoot; H Paulus; V Strand Journal: Arthritis Rheum Date: 1995-06
Authors: C Miceli-Richard; E Comets; C Verstuyft; R Tamouza; P Loiseau; P Ravaud; H Kupper; L Becquemont; D Charron; X Mariette Journal: Ann Rheum Dis Date: 2007-08-02 Impact factor: 19.103
Authors: A Ferreiro-Iglesias; A Montes; E Perez-Pampin; J D Cañete; E Raya; C Magro-Checa; Y Vasilopoulos; T Sarafidou; R Caliz; M A Ferrer; B Joven; P Carreira; A Balsa; D Pascual-Salcedo; F J Blanco; M J Moreno-Ramos; A Fernández-Nebro; M C Ordóñez; J J Alegre-Sancho; J Narváez; F Navarro-Sarabia; V Moreira; L Valor; R García-Portales; A Marquez; J Martin; J J Gómez-Reino; A Gonzalez Journal: Pharmacogenomics J Date: 2015-04-21 Impact factor: 3.550
Authors: Jeffrey R Curtis; Theresa McVie; Ted R Mikuls; Richard J Reynolds; Iris Navarro-Millán; James O'Dell; Larry W Moreland; S Louis Bridges; Veena K Ranganath; Stacey S Cofield Journal: J Rheumatol Date: 2013-04-15 Impact factor: 4.666
Authors: H Schotte; B Schlüter; S Drynda; P Willeke; N Tidow; G Assmann; W Domschke; J Kekow; M Gaubitz Journal: Ann Rheum Dis Date: 2004-09-02 Impact factor: 19.103