Metabolomic and lipidomic profiling of plasma in kidney stone patients: identification of potential biomarkers and therapeutic targets.

Background: Kidney stone are among the most common urologic diseases characterized with metabolic disorder. Biomarker for kidney stone detection and the metabolic variables in kidney stone development have attracted increasing attention.

Methods: To explore the metabolomic and lipidomic characteristics of plasma in patients with kidney stones, we collected plasma samples from 200 participants, including 100 kidney stone patients and 100 healthy controls. We designated 59 patients with clearly defined stone compositions alongside matched healthy individuals as the training set (n = 118), while the remaining 41 patients with unclear stone compositions were paired with healthy individuals and served as the test set (n = 82).

Results: A total of 333 and 270 metabolites were significantly altered in kidney stone patients under positive and negative ion modes, respectively, compared to healthy controls. KEGG analysis indicated that pathways such as Arginine and proline metabolism, Citrate cycle (TCA cycle), Alanine, aspartate and glutamate metabolism and phenylalanine metabolism, were closely associated with kidney stone formation. Moreover, a total of 416 lipids were significantly changed in the Kidney stone group and the control group. Using Lasso model, a panel of integrated 4 metabolites and 4 lipids showed effective discrimination between Kidney stone group and the control group. Among these metabolites, Isorhamnetin has the potential to effectively reduced oxalate-induecd acute kidney injury, hence lowering the likelihood of stone formation.

Conclusions: These findings offer novel insights into the metabolic and lipidomic alterations associated with kidney stones, providing potential biomarkers for early diagnosis and therapeutic targets for intervention.