Type 2 diabetes mellitus (T2DM), 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. 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. The rhesus macaque (Macaca mulatta) represents an ideal animal model for understanding the pathogenesis and complications of T2DM. As primates, rhesus macaques are more similar to humans than rodents, sharing 93% DNA sequence identity. With respect to T2DM in particular, the rhesus macaque is strikingly similar to humans. Like many groups of T2DM humans, laboratory-maintained ad libitum fed rhesus macaques develop T2DM with a lifetime incidence estimated to be around 30%. Clinically, T2DM rhesus macaques exhibit the same phenotype as T2DM humans: hyperglycemia, glycosuria, polydipsia, polyphagia, excess adiposity, dyslipidemia, insulin resistance, and impaired glucose tolerance. They also show the same metabolic disturbances and develop the same complications, including nephropathy, retinopathy, neuropathy, and other macrovascular changes. Given its well recognized applicability to many human diseases, including T2DM, and its recently published genome, the rhesus macaque is an exceptional model with which to understand T2DM pathogenesis and progression at the metabolic and metabolomic levels. Urine samples from a cohort of spontaneously T2DM rhesus macaques were compared with samples from normal counterparts to identify urinary metabolites capable of discriminating normal from T2DM monkeys. The kidney proximal tubule transporter, SLC6A20 (a Na+-dependent transporter), was implicated in the increased excretion of the urinary metabolites. Similar results were replicated in the db/db mouse model of T2DM. The combination of a unique nonhuman primate colony (rhesus macaque), genetically modified mice, and the latest in metabolomic technology provides a new perspective on the multifactorial T2DM phenotype. To enhance understanding of the metabolic indicators of 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. Metabolomics for urinary biomarker discovery in gamma irradiated rats. Identifying noninvasive biomarkers of ionizing radiation would permit rapid assessment and triage of exposed individuals for palliative and follow-up care. It may also facilitate the elucidation of novel molecular mechanisms associated with the ionizing radiation DNA damage and repair response. Historically biomarkers of radiation have been those related to DNA damage [e.g., gammaH2AX] and gene expression changes [e.g., XPC, CDKN1A, GADD45, MDM2], but small molecule indicators have not been explored or developed as extensively. A benefit of using small molecule screening (i.e., metabolomics) compared to other omics technologies such as proteomics, genomics or transcriptomics is that the data produced from the latter may not accurately reflect the current physiological status. Metabolites, as the end products of cellular processes, are likely to reflect any changes occurring at the epigenomic, genomic, proteomic or transcriptomic level. Furthermore, first pass assessment of exposed individuals with urinary biomarkers measured by miniaturized devices using differential mobility spectrometry can be done in the field quickly and accurately. Exposed individuals can then be assessed later using more time intensive gold standard biodosimetry approaches such as dicentric analysis. Radiation metabolomics has aided in the identification of a number of biomarkers in cells and mice. These markers have been shown to be both dose and time dependent. Metabolomics was used to analyze urine samples from rats over 7 days after either sham-irradiation or gamma-irradiation with 3 Gy. Using multivariate data analysis, nine urinary biomarkers of gamma radiation in rats were identified, including a novel mammalian metabolite, N-acetyltaurine. These upregulated urinary biomarkers were confirmed through tandem mass spectrometry and comparisons with authentic standards. They include thymidine, 2'deoxyuridine, 2'deoxyxanthosine, N(1) acetylspermidine, N-acetylglucosamine/galactosamine 6 sulfate, N acetyltaurine, N-hexanoylglycine, taurine and, tentatively, isethionic acid. Of these metabolites, 2'deoxyuridine and thymidine were previously identified in the rat by GCMS (observed as uridine and thymine) and in the mouse by UPLC-ESI-QTOFMS. 2'Deoxyxanthosine, taurine and N-hexanoylglycine were also seen in the mouse by UPLC-ESI-QTOFMS. These are now unequivocal cross-species biomarkers for ionizing radiation exposure. Downregulated biomarkers were shown to be related to food deprivation and starvation mechanisms. The metabolomics approach has aided in finding common biomarkers of ionizing radiation exposure.

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