Among the complex network of inflammatory cells involved in the pathogenesis of rheumatoid arthritis (RA), Th17 cells have recently been identified as key cells in the promotion of autoimmune processes, and joint destruction. The IL-23/Th17 signalling pathway, consisting of IL-23/IL-23R, IL-17A and IL-17F encoding genes, represents a candidate way for RA development with possible involvement in disease susceptibility and effect on disease progression. The present study aimed to determine the association between the polymorphic variants of the IL-17A (rs2275913), IL-17F (rs763780) and IL-23R (rs11209026) genes and RA susceptibility, progression and response to therapy with TNF-α inhibitors. Eighty-nine patients and 125 healthy individuals were investigated. The IL-17A polymorphism was found to affect RA progression and response to anti-TNF treatment. Female patients carrying the IL-17A wild-type genotype more frequently presented with stage 4 (8/24 vs. 6/47; p = 0.058) and were characterized by more active disease (the highest DAS28 score >5.1) after 3 months of therapy with the TNF inhibitors (12/23 vs. 15/45; p = 0.040). The IL-17F polymorphism appeared to be associated with susceptibility to the disease. The presence of the IL-17F minor variant (OR 3.97; p < 0.001) and its homozygosity (OR 29.62; p < 0.001) was more frequent among patients than healthy individuals. These results suggest that the polymorphisms within the IL-17A and IL-17F genes play a significant role in RA.
Rheumatoid arthritis is a chronic autoimmune-based inflammatory disease that leads to progressive joint degeneration, disability, and an increased risk of cardiovascular complications, which is the main cause of mortality in this population of patients. Although several biomarkers are routinely used in the management of rheumatoid arthritis, there is a high demand for novel biomarkers to further improve the early diagnosis of rheumatoid arthritis, stratification of patients, and the prediction of a better response to a specific therapy. In this study, the metabolomics approach was used to provide relevant biomarkers to improve diagnostic accuracy, define prognosis and predict and monitor treatment efficacy. The results indicated that twelve metabolites were important for the discrimination of healthy control and rheumatoid arthritis. Notably, valine, isoleucine, lactate, alanine, creatinine, GPC APC and histidine relative levels were lower in rheumatoid arthritis, whereas 3-hydroxyisobutyrate, acetate, NAC, acetoacetate and acetone relative levels were higher. Simultaneously, the analysis of the concentration of metabolites in rheumatoid arthritis and 3 months after induction treatment revealed that L1, 3-hydroxyisobutyrate, lysine, L5, acetoacetate, creatine, GPC+APC, histidine and phenylalanine were elevated in RA, whereas leucine, acetate, betaine and formate were lower. Additionally, metabolomics tools were employed to discriminate between patients with different IL-17A genotypes. Metabolomics may provide relevant biomarkers to improve diagnostic accuracy, define prognosis and predict and monitor treatment efficacy in rheumatoid arthritis.
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