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Sökning: WFRF:(Vosslamber Saskia)

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  • Luebbers, Joyce, et al. (författare)
  • The type I IFN signature as a biomarker of preclinical rheumatoid arthritis
  • 2013
  • Ingår i: Annals of the Rheumatic Diseases. - London : BMJ Publishing Group. - 0003-4967 .- 1468-2060. ; 72:5, s. 776-780
  • Tidskriftsartikel (refereegranskat)abstract
    • Objectives To validate the presence and demonstrate the clinical value of the type I interferon (IFN)-signature during arthritis development. Method In 115 seropositive arthralgia patients who were followed for the development of arthritis (Amsterdam Reade cohort), and 25 presymptomatic individuals who developed rheumatoid arthritis (RA) later, and 45 population-based controls (Northern Sweden cohort), the expression levels of 7 type I IFN response genes were determined with multiplex qPCR and an IFN-score was calculated. The diagnostic performance of the IFN-score was evaluated using Cox regression and Receiver Operating Characteristics (ROC)-curve analysis. Results In 44 of the 115 at-risk individuals (38%) from the Amsterdam Reade cohort, arthritis developed after a median period of 8 months (IQR 5-13). Stratification of these individuals based on the IFN-score revealed that 15 out of 25 IFNhigh individuals converted to arthritis, compared with 29 out of 90 IFNlow individuals (p=0.011). In the Northern Sweden cohort, the level of the IFN-score was also significantly increased in presymptomatic individuals who developed RA compared with population-based controls (p=0.002). Cox regression analysis of the Amsterdam Reade cohort showed that the hazard ratio (HR) for development of arthritis was 2.38 (p=0.008) for IFNhigh at-risk individuals after correction for anticitrullinated protein antibodies (ACPA) and rheumatoid factor (RF). The ROC-curve area under the curve (AUC) for the IFN-score combined with ACPA and RF in the prediction of arthritis was 78.5% (p=0.0001, 95% CI 0.70 to 0.87). Conclusions The results demonstrated clinical utility for the IFN-signature as a biomarker in the prediction of arthritis development.
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