Lee, BM; Lim, SK; Han, EY; Bae, JY; Ahn, IY; Kwon, MJ; Kim, SM; Cho, MC;
Purpose: To discover potential biomarkers for nephrotoxicity by using the profiling analysis of toxicogenomics and toxicometabolomics. Methods: Data were collected from various sources of databases and used for identifying biomarkers for nephrotoxicity. For the correlation analysis, metabolic profiling in urine and gene expression profiling in kidney tissues in vivo were employed and area under the curve (AUC) values by Receiver Operating Characteristics (ROC) program (Medcalc) were used for ranking potential biomarkers for nephrotoxicity. DAVID tool and the Small Molecule Pathway Database (SMPDB) were used for pathway analysis of genes and metabolites. Results of the study: Data analysis showed that pathways of regulated metabolites included methionine metabolism, glycine, serine and threonine metabolism, Ammonia recycling, Betaine metabolism, fatty acid biosynthesis, purine metabolism, tyrosine metabolism, arginine and proline metabolism, bile acid biosynthesis, catecholamine biosynthesis and valine, leucine and isoleucine degradation. These major pathways were all significantly involved more than 2%. And in these pathways, glycine, serine and threonine metabolism, arginine and proline metabolism and valine, leucine and isoleucine degradation were overlapped with genomic pathways. Metabolites were ranked in order of acetate, dimethylglycine, citrate and 2-oxoglutarate. These metabolites had AUC value greater than 0.75. Acetate, citrate and 2-oxoglutarate were included in citrate cycle, and dimethylglycine was included in glycine, serine and threonine metabolism with high significance. A gene closely related to dimethylglycine was bhmt (betaine-homocysteine S-methyltransferase), which showed the pattern of down-regulation and concurrently dimethylglycine was up-regulated in urine in vivo.