Objective To investigate the metabolic characteristics of gouty arthritis (GA) with dampness syndrome (GA-DS), to identify potential diagnostic and recurrence-predictive biomarkers, and to preliminarily elucidate the underlying mechanisms of the effect of traditional Chinese medicine (TCM) dampness syndrome on metabolic abnormalities in patients with gout.

Methods The study was conducted as part of a clinical trial—Clinical Cohort Construction and Efficacy Evaluation of Gouty Arthritis With Dampness Syndrome, which has been registered in the Chinese Clinical Trial Registry (ChiCTR) and assigned the registration number of ChiCTR2000038969. Healthy controls (HC), patients with GA-DS, and those with GA with non-dampness syndrome (GA-NDS) were enrolled. Clinical assessments of metabolic and inflammatory parameters were performed, and targeted metabolomic profiling of plasma samples was conducted. Diagnostic and recurrence prediction models were constructed using random forest and logistic regression, and the efficacy of the recurrence model was validated in an independent cohort.

Results GA-DS patients exhibited significant metabolic disturbances, with significantly elevated levels of body mass index (BMI), serum uric acid (SUA), and lipid metabolism indicators. Metabolomic analysis revealed significantly elevated plasma acetovanillone and cyclic adenosine monophosphate (cAMP) in the GA-DS group compared with those in the HC and GA-NDS groups (all q < 0.05). These two metabolites were significantly correlated with SUA and the inflammatory marker C-reactive protein levels (r = 0.50 and r = 0.48, respectively; both P < 0.05). A logistic regression model based on acetovanillone and cAMP effectively distinguished GA-DS patients from HC and GA-NDS patients (out-of-bag error: 0.158 ± 0.038; accuracy: 84.2 ± 6.6%; adjusted P < 0.001 for both indicators vs. those of the other models). Further analysis showed that cAMP and ureidosuccinic acid levels increased in patients who later experienced GA recurrence (P < 0.05), with detectable changes as early as 24 weeks before recurrence. A recurrence prediction model combining cAMP and creatine kinase-MB (CK-MB) achieved the best performance and was validated in an independent cohort (accuracy: 67.39%, 95% CI: 52.0%-80.5%; area under the curve AUC = 0.803, 95% CI: 0.676-0.930).

Conclusion GA-DS patients display distinct metabolic abnormalities. Acetovanillone and cAMP hold promise as diagnostic biomarkers, while cAMP in combination with CK-MB can be used for the early prediction of the risk of GA-DS recurrence. These findings provide novel insights into the metabolic basis of TCM dampness syndrome and offer potential biomarkers for early diagnosis and stratification of recurrence risk in GA.