Rheumatoid arthritis (RA) is a chronic progressive disease, it often involves kidney, lung, heart, and other systems.Renal damage is quite common in RA. Exploring of biomarkers of renal damage in the course of RA progression is of significant importance for disease diagnosis and treatment. We use type II Collagen-Induced Arthritis(CIA) Model. Serums were collected at the 4th, 6th, 8th, and 10th week after the first immunization. An untargeted metabonomic strategy based on UPLC-Q/TOF/MS with support vector machine(SVM) was developed to discover the biomarkers in the rats' serum samples between the RA stage(4-6 weeks in RA model, at which time the kidneys are not affected) and renal damage in RA stage(8-10 weeks in RA model, and the kidneys are affected). Principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were used to analyze the metabolic profiles of rat serum. The support vector machine (SVM) method was used to screen the specific markers of renal damage in RA. Following multivariate statistical and integration analysis, 5 specific markers of renal damage in RA were screened and found. After the analysis of these metabolites, pentose and glucuronate interconversions are closely related to the pathogenesis of RA renal damage. The present study first use untargeted dmetabonomics combined with the pathological features in the different phases of CIA model rats. This will provide a basis for the choice of treatment drugs for patients with RA who may be complicated by renal damage.
Keywords: Biomarkers; Metabonomics; Renal damage; Rheumatoid arthritis.
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