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sRAGE, S100 proteins and PTPN22 C1858T genetic polymorphism in rheumatoid arthritis

Rheumatoid arthritis is a chronic inflammatory autoimmune disease. Measurement of the level of serum markers (sRAGE, S100A9, S100A8 and S100A12) and genetic testing for the presence of the PTPN22 genetic polymorphism could help elucidate the underlying cause of inflammation and complications in RA, such as atherosclerosis. Therefore, serum levels of sRAGE, S100A9, S100A8 and S100A12 were measured by ELISA in patients with established RA (n=138). The associations between the serum levels of these molecules; and inflammatory markers and RA complications were analysed by multiple linear regression modelling. Established RA patients (n=192) were investigated for the PTPN22 C1858T genetic polymorphism by PCR-RFLP. Multiple logistic regression modelling was used to examine the association between PTPN22 C1858T genetic polymorphism and inflammatory markers and RA complications. In RA patients, we found that serum levels of S100A9 were associated with the body mass index (BMI); and the presence of S100A8 and S100A12. The serum levels of S100A8 in RA patients were associated with the presence of anti-citrullinated peptide antibodies, rheumatoid factor and S100A9. The serum levels of S100A12 in RA patients were associated with the presence of anti-citrullinated peptide antibodies and S100A9; and a history of diabetes. Inflammatory markers and RA complications were not associated with the PTPN22 genetic polymorphism in established RA patients; serum level of triglyceride was the only variable associated with PTPN22 C1858T in multiple logistic regression analysis. Taken together, these data suggest that serum levels of sRAGE, S100A9 and S100A12 protein may be useful correlates of inflammation and autoantibody production in RA patients. Further studies are recommended to determine whether these markers predict clinical outcomes when measured at the onset of RA.

Identiferoai:union.ndltd.org:ADTP/286216
CreatorsYueh-Sheng Chen
Source SetsAustraliasian Digital Theses Program
Detected LanguageEnglish

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