A Metabolomic Signature Predicts Gout Flare Clinical Outcome Associated with Colchicine Prophylaxis

Objective This study investigated that serum metabolomics, prior to ULT initiation, could serve as a biomarker for responsiveness to colchicine prophylaxis in patients with gout commencing treat‐to‐target ULT. Methods We studied a multicenter prospective cohort (n=409) initiating treat‐to‐target ULT plus colchicine prophylaxis. Untargeted metabolomics were measured at enrollment. We defined putative colchicine‐response or colchicine non‐response as no‐flare, or > 1 flare, respectively, during 6 months after first colchicine dose. Cox regression and machine learning models defined the metabolomic signatures associated with reported flare activity on colchicine prophylaxis in the cohort. Results In our cohort, 36.9% participants experienced at least one flare. Many inflammation‐related metabolites were differentially abundant in the recurrent flare group and correlated with recurrent flare risk. A significant association was found between a four‐metabolite risk score and gout flare activity (adjusted hazard ratio 3.21, 95% CI 2.24‐4.59), independent of the adjusted clinical factors. The machine learning model, which incorporated the top‐ranked metabolites selected by MUVR along with traditional clinical factors, reached an area under the receiver operating characteristic of 0.771 (95% CI 0.713‐0.828) and 0.724 (95% CI 0.611‐0.837) for predicting flare risk in the discovery and validation cohort, respectively. Conclusions Metabolomic profile‐defined inflammation status was associated with gout flare outcomes in ULT initiators receiving colchicine prophylaxis. Identification of these novel metabolomic predictive signatures prior to ULT could potentially help optimize clinical decision‐making for flare prophylaxis colchicine dosing and duration in the first 6 months after initiation of treat‐to‐target ULT in gout.