Metabolomic Dataset - EAR study

Rheumatoid arthritis (RA) is a chronic autoimmune disease that affects millions of people worldwide, and early detection is crucial for effective treatment and management. Metabolomics, the study of small molecules in biological systems, has the potential to provide important insights into the early diagnosis and treatment of RA. One promising area of metabolomics research in RA is the identification of early biomarkers. By analyzing metabolic changes that occur in the serum of RA patients naïve to treatment we have identified a panel of 3 metabolites: glyceric acid, lactic acid, and 3-hydroxyisovaleric acid as the best metabolite combination for early RA diagnosis (ERA) identifying patients with 96.7% of certainty outperforming the classical anti-cyclic citrullinated peptide marker by 2.9% and the C-reactive protein inflammatory marker by 15.4%. This early detection could allow for early intervention and treatment, potentially preventing the progression of the disease. Additionally, the deregulated metabolites have been associated with alterations in pathways related to amino acid metabolism such as aminoacyl-tRNA biosynthesis and the metabolism of serine, glycine, and phenylalanine that can be used to identify potential targets for therapeutic intervention.