Unraveling the heterogeneity of hyperuricemia using untargeted metabolomics and statistical modeling

Abstract

Hyperuricemia is the second most prevalent metabolic disorder globally and exhibits pronounced heterogeneity in clinical practice. Only about 10% of individuals with asymptomatic hyperuricemia (HUA) progress to gout, yet the lack of specific biomarkers and precise therapeutic targets hinders accurate prediction of disease progression. This work focuses on investigating the heterogeneity of hyperuricemia, aiming to elucidate potential mechanisms underlying its transition from asymptomatic to symptomatic stages. A total of 107 serum samples were analyzed, including 36 healthy controls (Con), and 30, 32 and 9 patients with HUA, gouty arthritis (gout), and gout complicated by uric acid nephrolithiasis (UAN), respectively. Using an advanced SCIEX ZenoTOF 7600-based untargeted metabolomics platform, 925 metabolites were identified in both positive and negative ionization modes. The assessment of quality control (QC) samples showed high precision in instrumental measurement with RSD values of the ion features less than 30% achieving 91.76% and 89.73% respectively in the two ionization modes. A total of 46, 37, 28, and 26 differential metabolites were identified among the four groups. Among them, four metabolites showed high sensitivity and specificity in the analysis of the first three groups. Five metabolic pathways remained consistently dysregulated throughout disease progression, which indicates their potential as mechanistic drivers. These findings provide novel biological insights for the early diagnosis and precision treatment of gout and its complications, and offer a crucial foundation for understanding the metabolic basis of hyperuricemia heterogeneity.