A serum metabolic biomarker panel for early rheumatoid arthritis

Abstract

Objective: There is an urgent need for novel biomarkers to improve the early diagnosis of rheumatoid arthritis (ERA). Current serum biomarkers used in the management of ERA, including rheumatoid factor and anti-cyclic citrullinated peptide (ACPA), show limited specificity and sensitivity. Here, we used metabolomics to uncover new serum biomarkers of ERA. Methods: We applied an untargeted metabolomics approach including gas chromatography time-of-flight mass spectrometry in serum samples from an ERA cohort (n=32) and healthy controls (n=19). Metabolite set enrichment analysis was performed to explore potentially important biological pathways. Partial least squares discriminant analysis and variable importance in projection analysis were performed to construct an ERA biomarker panel. Results: Significant differences in the content of 11/81 serum metabolites were identified in patients with ERA. Receiver operating characteristic (ROC) analysis showed that a panel of only three metabolites (glyceric acid, lactic acid, and 3-hydroxisovaleric acid) could correctly classify 96.7% of patients with ERA, with an area under the ROC curve of 0.963 and with 94.4% specificity and 93.5% sensitivity, outperforming ACPA-based diagnosis by 2.9% and, thus, improving the preclinical detection of ERA. Aminoacyl-tRNA biosynthesis and serine, glycine, and phenylalanine metabolism were the most significant dysregulated pathways in patients with ERA. Conclusion: A metabolomics serum-based biomarker panel composed of glyceric acid, lactic acid, and 3-hydroxisovaleric acid offers potential for the early clinical diagnosis of RA.