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The aim is to discover plasma metabolomic markers to predict RA onset, assess disease activity, and forecast treatment efficacy. The study includes 209 established RA patients who are disease\u2010modifying antirheumatic drugs\u2010free for six months prior to enrollment, with 197 of them followed for 3\u20136 months to assess treatment response. Additionally, 56 individuals at risk are recruited, with 34 completing a 5\u20137\u2010year follow\u2010up. Analysis reveals that metabolites related to methylation and redox imbalance, such as S\u2010adenosylmethionine, sarcosine, nicotinamide adenine dinucleotide, glutathione, etc., are associated with RA development and severity, and contribute to its heterogeneity across age, sex, and anti\u2010citrullinated protein autoantibody status. Ridge regression models are constructed using metabolite and clinical features for the response to methotrexate (MTX) plus leflunomide, achieving an average receiver operating characteristic (ROC) score of 0.83, and for the MTX plus hydroxychloroquine, achieving an average ROC score of 0.92. 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