Plasma Metabolomics Reveals a Shared Metabolomic Profile in Experimental and Human Chronic Kidney Disease.

Chronic kidney disease (CKD) affects nearly 10% of the global population, yet diagnosis and disease monitoring still rely primarily on plasma creatinine. Because creatinine levels are strongly influenced by non-renal factors, such as age, sex, muscle mass, and diet, its accuracy as a kidney function marker is limited. To identify plasma biomarkers that reflect kidney injury, we applied untargeted and targeted metabolomics in the adenine-induced CKD mouse model, a well-known tubular damage model, and validated the findings in plasma from patients with advanced CKD and healthy controls. We identified five metabolites that showed altered plasma levels in both experimental and human CKD, of which galactonic acid, pipecolic acid, and N-acetylneuraminic acid were significantly associated with measured glomerular filtration rate (GFR). As a proof-of-concept, we demonstrated that integrating these metabolites into a biomarker panel alongside creatinine could improve GFR estimation compared with creatinine alone. Our study introduces a promising metabolite-based biomarker panel that might enhance the accuracy of kidney function assessment and could potentially support diagnosis, risk stratification, and monitoring of disease progression; however, validation in a broader CKD cohort is needed.