Serum metabolomics study reveals a distinct metabolic diagnostic model for renal calculi.

Renal calculi (RC) represent a prevalent disease of the urinary system characterized by a high incidence rate. The traditional clinical diagnosis of RC emphasizes imaging and stone composition analysis. However, the significance of metabolic status in RC diagnosis and prevention remains unclear. This study aimed to investigate serum metabolites in RC patients to identify those associated with RC and to develop a metabolite-based diagnostic model. We employed nontargeted metabolomics utilizing ultra-performance liquid chromatography‒mass spectrometry (UPLC‒MS) to compare serum metabolites between RC patients and healthy controls. Our findings demonstrated significant disparities in serum metabolites, particularly in fatty acids and glycerophospholipids, between the two groups. Notably, the glycerophospholipid (GP) metabolic pathway in RC patients was significantly disrupted. Logistic regression models using differentially abundant metabolites revealed that elevated levels of 2-butyl-4-methyl phenol and reduced levels of phosphatidylethanolamine (P-16:0/22:6(4Z,7Z,10Z,13Z,16Z,19Z)) had the most substantial effect on RC risk. Overall, our study indicates that RC induces notable alterations in serum metabolites and that the diagnostic model based on these metabolites effectively distinguishes RC. This research offers promising insights and directions for further diagnostic and mechanistic studies on RC.