Key result
The multi-omics biomarker model combining six serum metabolites achieved an AUC of 0.987 in the discovery cohort and 0.997 in the validation cohort to accurately distinguish DHG patients from healthy controls.
Why the study?
The ambiguity of damp-heat gout's pathomechanism and the lack of quantifiable indicators limit its clinical accurate diagnosis and treatment.
Does integrated multi-omics analysis identify diagnostic biomarkers and therapeutic targets in patients with damp-heat gout compared to healthy controls?
Does integrated multi-omics analysis identify diagnostic biomarkers and therapeutic targets in patients with damp-heat gout compared to healthy controls?
Effect estimate: AUC 0.987 (discovery cohort); AUC 0.997 (validation cohort)
Integrated metabolomic and proteomic analyses identified a six-biomarker panel with high diagnostic efficacy for damp-heat gout, providing novel targets for clinical diagnosis and therapy.
Damp-heat gout (DHG) is a highly certified type of disease integrated with syndrome in TCM. The ambiguity of its pathomechanism and the lack of quantifiable indicators limit its clinical accurate diagnosis and treatment. This study aimed to elucidate the pathological mechanism of DHG and establish a symptom-centered diagnostic and therapeutic model. We recruited 136 participants, comprising healthy controls (HCs) and DHG patients. Serum metabolomics and proteomics analyses were performed to screen common pathways. Based on the biological significance of these common pathways, a symptom-pathway correlation network was constructed to clarify the pathological mechanisms driving DHG occurrence and progression. Enrichment scores and correlations with key DHG symptoms were used to identify critical pathways. Differential metabolites and proteins associated with these critical pathways served to establish a multi-index diagnostic model and identify potential therapeutic protein targets. Integrated metabolomic and proteomic analyses revealed 21 common pathways associated with DHG. Four crucial pathways, such as Bile secretion, Cholesterol metabolism, Purine metabolism, Arachidonic acid metabolism, were exhibited significant correlations with core DHG symptoms. Furthermore, six pathway-related biomarkers were identified: Hypoxanthine, Prostaglandin E2, Uric acid, Deoxycholic acid, Taurochenodeoxycholic acid, and Bilirubin. The combined diagnostic efficacy of these biomarkers was optimal (discovery cohort: AUC = 0.987; validation cohort: AUC = 0.997). Six protein targets were identified from the crucial pathways, including ATP1A1, APRT, ANGPTL4, GLUT1, PTGES3 and LIPA. This study establishes a symptom-centered diagnostic and therapeutic model for DHG utilizing the identified biomarkers and clarifies the involvement of critical metabolic pathways in DHG pathogenesis, providing novel targets for improved clinical diagnosis and therapy.
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Yang et al. (2026) studied Male patients aged 18-70 diagnosed with dampness-heat gout (DHG) fulfilling the 2015 ACR/EULAR classification criteria for gouty arthritis and diagnostic standards for DHG per integrated traditional Chinese and Western medicine guidelines (n=136). Multi-omics biomarker diagnostic model based on six serum biomarkers: Hypoxanthine, Prostaglandin E2, Uric acid, Deoxycholic acid, Taurochenodeoxycholic acid, Bilirubin vs. Healthy controls without DHG was evaluated on Diagnostic accuracy for distinguishing DHG patients from healthy controls using six biomarkers combined (AUC 0.987 (discovery cohort); AUC 0.997 (validation cohort)). The multi-omics biomarker model combining six serum metabolites achieved an AUC of 0.987 in the discovery cohort and 0.997 in the validation cohort to accurately distinguish DHG patients from healthy controls.
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