Gout and Hyperuricemia Have Distinct Serum Metabolomic Signatures

test tubes
test tubes
Researchers studied metabolic alterations and dysregulated metabolic pathways in hyperuricemia and gout, and discovered potential metabolite biomarkers to differentiate between gout and asymptomatic hyperuricemia.

Gout and hyperuricemia have distinct serum metabolic biomarkers, a finding that may help in the early diagnosis of gout or the prediction of progression from hyperuricemia to gout, according to study results published in Arthritis & Rheumatology.

Hyperuricemia is a major risk factor for gout. Because most patients with hyperuricemia are asymptomatic, developing novel prognostic markers may improve the potential for early diagnosis of gout and improve care accordingly.

The objective of the current study was to assess serum metabolomics and dysregulated metabolic pathways in hyperuricemia and gout, and to identify diagnostic metabolic biomarkers using high-resolution mass spectrometry to distinguish gout from hyperuricemia.

The study sample included 330 patients from the Gout Clinic of the Affiliated Hospital of Qingdao University, Qingdao, China. Of these patients, 109 were previously diagnosed with gout and 102 had asymptomatic hyperuricemia; 119 individuals with normal serum uric acid levels were included in the study as control participants.

According to the metabolomic profile analysis, several pathways were significantly dysregulated in patients with hyperuricemia and gout compared with control participants; among the dysregulated pathways in hyperuricemia and gout, altered arginine metabolism seems to have a major role. Additional pathways perturbed significantly between patients with gout and control participants included glycine, serine and threonine metabolism, proline metabolism, arginine biosynthesis, ascorbate and aldarate metabolism, D-glutamine and D-glutamate metabolism, alanine, aspartate and glutamate metabolism, phenylalanine, tyrosine and tryptophan biosynthesis.

To distinguish gout from hyperuricemia, 7 metabolites were identified as potential biomarkers, including uracil, trigonelline, betaine, pipecolic acid, myristic acid, arachidonate, glycocholate. A prediction model based on these metabolites to distinguish gout from asymptomatic hyperuricemia had good sensitivity and specificity.

The 4 metabolic pathways – arginine and proline metabolism, taurine and hypotaurine metabolism, ascorbate and aldarate metabolism, and alanine, aspartate and glutamate metabolism – were found to be interconnected primarily through amino acids, among which arginine and proline metabolism appeared to be the key node linking other 3 metabolic pathways differentiating patients with hyperuricemia from the control participants.

The study had several limitations, including the cross-sectional design, exclusion of patients with common comorbidities linked to hyperuricemia, and the possibility that altered metabolites in serum may reflect inflammatory and metabolic changes in other organs.

“[O]ur study has exemplified the power of combining metabolomics and machine learning algorithms for identifying potential metabolic biomarkers to distinguish gout from asymptomatic [hyperuricemia],” the researchers concluded.

Disclosure: Several study authors declared affiliations with the pharmaceutical industry. Please see the original reference for a full list of authors’ disclosures.


Shen X, Wang C, Liang N, et al. Serum metabolomics identifies dysregulated pathways and potential metabolic biomarkers for hyperuricemia and gout. Arthritis Rheumatol. Published online March 24, 2021. doi:10.1002/art.41733