To enhance understanding of the metabolic indicators of type 2 diabetes mellitus (T2DM) disease pathogenesis and progression, the urinary metabolomes of well characterized rhesus macaques (normal or spontaneously and naturally diabetic) were examined. High-resolution ultra-performance liquid chromatography coupled with the accurate mass determination of time-of-flight mass spectrometry was used to analyze spot urine samples from normal (n ؍ 10) and T2DM (n ؍ 11) male monkeys. The machine-learning algorithm random forests classified urine samples as either from normal or T2DM monkeys. The metabolites important for developing the classifier were further examined for their biological significance. Random forests models had a misclassification error of less than 5%. Metabolites were identified based on accurate masses (<10 ppm) and confirmed by tandem mass spectrometry of authentic compounds. Urinary compounds significantly increased (p < 0.05) in the T2DM when compared with the normal group included glycine betaine (9-fold), citric acid (2.8-fold), kynurenic acid (1.8-fold), glucose (68-fold), and pipecolic acid (6.5-fold). When compared with the conventional definition of T2DM, the metabolites were also useful in defining the T2DM condition, and the urinary elevations in glycine betaine and pipecolic acid (as well as proline) indicated defective re-absorption in the kidney proximal tubules by SLC6A20, a Na ؉ -dependent transporter. The mRNA levels of SLC6A20 were significantly reduced in the kidneys of monkeys with T2DM. These observations were validated in the db/db mouse model of T2DM. This study provides convincing evidence of the power of metabolomics for identifying functional changes at many levels in the omics pipeline.Type 2 diabetes mellitus (T2DM), 4 the most common type of diabetes, is a significant, costly, and rapidly expanding public health concern worldwide. T2DM is associated with microvascular (nephropathy, retinopathy, and neuropathy) and macrovascular (coronary artery disease and peripheral vascular disease) pathologies resulting in a complex, multifactorial metabolic phenotype. Therefore, understanding the molecular pathogenesis and progression of T2DM, its associated and varied complications, and its effects on numerous organ systems is not trivial. The emerging field of small molecule profiling, or metabolomics, has already provided new perspectives on T2DM (1-5). As the end products of all cellular processes, global metabolite profiling may represent the best and largest net with which to capture changes originating from epigenomic, genomic, transcriptomic, and proteomic alterations.Metabolomics aims to identify and quantify all small molecules as they may be the most accurate indicators of cellular physiology (6). Moreover, metabolomics is an NIH Roadmap Initiative and was listed as a research priority in the American Society of Nephrology Renal Research Report (7). Metabolomic studies of T2DM have utilized a variety of animal models (e.g. db/db mice, streptozotocin-treated mice, Zucker...