Metabolomics in chronic kidney disease: from experimental model to human disease

Chronic kidney disease (CKD) high global prevalence, estimated between 11 to 13%, has been recognized as a mayor health challenge for healthcare systems due to its relevant economic and social implications. Main medical intervention strategies are directed to delay the progression of CKD and prevent outcomes. Serum creatinine concentration has been used to classify CKD and define its progression stage; however, it is well known the low sensitivity shown by this test. This fact has conducted to the search for new markers in order to improve the disease diagnosis, monitoring and treatment. In this context, metabolomics science and animal models have allowed identification of new metabolites that can be used as future biomarkers into clinical practice. This review aims to summarize the metabolomics profiles reported in different experimental models and clinical research on CKD. According with the data obtained, metabolites related with quaternary amines and aminoacid metabolic pathways like TMNO, indoxyl sulfate and dimethylarginine, suggest a promising alternative for identification, classification and prognosis of CKD.