Wilson’s disease (WD) is an inherited disorder that leads to copper accumulation, but the detailed pathogenic mechanism is uncertain and diagnosis can be difficult without genetic testing because of similarities to other more common diseases.To investigate the metabolomic features of WD, and elucidate its difference with other normal copper metabolism disease.We performed targeted and untargeted metabolomic profiling using ultra-high performance liquid chromatography-tandemmassspectrometry (UPLC-MS/MS) and liquid chromatography-tandemmassspectrometry (LC-MS).We compared the metabolomic profiles of two subgroups of WD patients, hepatic WD(H-WD)and neurological WD (N-WD); of H-WD patients and liver cirrhosis patients (who have similar symptoms, but normal copper levels);and of N-WD patients and Parkinson’s disease patients (who have similar symptoms, but normal copper levels). Pairwise comparisons indicated distinctive metabolomic profiles for male and female WD patients, H-WD and N-WD patients, N-WD and Parkinson’s disease patients, and H-WD and liver cirrhosis patients. We then used logistic regression analysis, receiver operating characteristic (ROC) analysis, and model construction to identify candidate diagnostic biomarkers that distinguish H-WD from liver cirrhosis, and N-WD from Parkinson’s disease. Based on the spatial distribution of the data obtained by PLS-DA analysis, we found that there are different hydrophilic metabolites (aminoacyl-tRNA biosynthesis; alanine, aspartate, and glutamate metabolism; phenylalanine metabolism; arginine biosynthesis; and nicotinate and nicotinamide) and lipophilic metabolites (TG(16:0_16:1_22:6), TG(16:0_16:0_22:6) and TG(16:0_16:1_22:5)) between H-WD and N-WD. Furthermore, WD patients have metabolic characteristics that distinguish it from other analogous diseases (liver cirrhosis and Parkinson's disease). Through analysis, WD showed significant differences in the levels of metabolites in some critical metabolism pathways and in the levels of many lipids. ROC analysis indicated that 3 metabolites may be considered as candidate biomarkers for diagnosing WD.