Background: Gout is a metabolic disease and is the most common form of inflammatory arthritis affecting men. However, the pathogenesis of gout is still uncertain, and novel biomarkers are needed for early prediction and diagnosis of gout. To reveal the metabolic alterations in plasma of gout patients and hyperuricemia patients and discover novel molecular biomarkers for early diagnosis. Metabonomics was employed to screen and identify novel biomarkers of gout based on human plasma. High performance liquid chromatography-diode array detector (HPLC-DAD) and orthogonal signal correction partial least squares discriminate analysis (OPLS-DA) were also used for metabonomics study.Results: 80 and 62 features were selected as remarkable significant variables in the two modes between gout and control group, 90 and 50 features between hyperuricemia (HUA) and control group, 63 and 60 features between gout and HUA group, respectively. 25 potential metabolic biomarkers which at least in two comparison groups were remained. Among 25 metabolites, 34% presented high area under the curve (AUC) values (AUC >0.75). Four metabolites including Lys-Ser, L-Pipecolic acid, glycine, arecoline were screened out. They were used to distinguish gout from hyperuricemia with AUC>0.75, which was greater than the AUC of uric acid.Conclusion: The differential metabolites of gout screened out were involved in amino acid metabolism, including glycine, serine and threonine metabolism, arginine biosynthesis, glutathione metabolism. Lys-Ser, L-pipecolic acid, glycine, arecoline were down-regulated in gout patients compared with hyperuricemia patients. The metabolomics signatures could serve as an efficient tool for early diagnosis and provide novel insights into the pathogenesis of gout.