Potential urinary and plasma biomarkers of peroxisome proliferation in the rat: identification ofN-methylnicotinamide andN-methyl-4-pyridone-3-carboxamide by1H nuclear magnetic resonance and high performance liquid chromatography

nists have been characterized largely in terms of their effects on lipids and glucose metabolism, whereas little has been reported about effects on amino acid metabolism. We studied responses to the PPAR␣ agonist WY 14,643 (30 mol⅐ kg Ϫ1 ⅐ day Ϫ1 for 4 wk) in rats fed a saturated fat diet. Plasma and urine were analyzed with proton NMR. Plasma amino acids were measured using HPLC, and hepatic gene expression was assessed with DNA arrays. The high-fat diet elevated plasma levels of insulin and triglycerides (TG), and WY 14,643 treatment ameliorated this insulin resistance and dyslipidemia, lowering plasma insulin and TG levels. In addition, treatment decreased body weight gain, without altering cumulative food intake, and increased liver mass. WY 14,643 increased plasma levels of 12 of 22 amino acids, including glucogenic and some ketogenic amino acids, whereas arginine was significantly decreased. There was no alteration in branched-chain amino acid levels. Compared with the fat-fed control animals, WY 14,643-treated animals had raised plasma urea and ammonia levels as well as raised urine levels of N-methylnicotinamide and dimethylglycine. WY 14,643 induced changes in a number of key genes involved in amino acid metabolism in addition to expected effects on hepatic genes involved in lipid catabolism and ketone body formation. In conclusion, the present results suggest that, in rodents, effects of pharmacological PPAR␣ activation extend beyond control of lipid metabolism to include important effects on whole body amino acid mobilization and hepatic amino acid metabolism.peroxisome proliferator-activated receptor-␣ PEROXISOME PROLIFERATOR-ACTIVATED RECEPTOR-␣ (PPAR␣) agonists are used clinically to treat dyslipidemia and to reduce the risk of cardiovascular complications (7). The beneficial effects of these agents appear to be most significant in patients with insulin resistance and diabetes (32). It is clear that a major and primary action of PPAR␣ activation is the transcriptional regulation of genes involved in lipid metabolism (36). However, the effects of PPAR␣ activation may not be limited to lipid metabolism, given the established interactions between the major substrate classes (19), e.g., the glucose-fatty acid cycle (29) and the glucose-alanine cycle (10). In terms of glucose metabolism, an important physiological role of PPAR␣ is suggested by the hypoglycemia in response to prolonged fasting developed by mice lacking PPAR␣ (17). Furthermore, treatment of fat-fed rats with the selective PPAR␣ agonist WY 14,643 resulted in increases in whole body and skeletal muscle insulin-stimulated glucose utilization, with the enhancement in muscle insulin sensitivity related to the degree of reduction in local lipid accumulation (39). Surprisingly little has been reported concerning effects of PPAR␣ activation on amino acid metabolism, although work based largely on analysis of mRNA in mouse liver (23) suggests an important influence on the handling of this substrate class.The aim of the present study was to provide...

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“…These findings concerning tryptophan metabolism confirm the results of previous studies of PPAR␣ agonists in rodents (31,37).…”

Section: Discussionsupporting

confidence: 82%

Beyond lipids, pharmacological PPARα activation has important effects on amino acid metabolism as studied in the rat

Sheikh

Camejo²,

Lanne³

et al. 2007

American Journal of Physiology-Endocrinology and Metabolism

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“…Changes in other metabolites, such as hypotaurine and proline, were linked to the disturbances in osmotic regulation. The change of adenosine, a nucleotide, may be related to peroxisome proliferation, as reported by Ringeissen et al (2003). At the reduced salinity of 23.3, differential metabolic responses relative to the metabolic profi les of samples from normal seawater were detected after arsenic exposure, including decreased branched-chain amino acids, threonine, ATP and adenosine.…”

Section: Differential Metabolic Responses In Digestive Gland From Clamentioning

confidence: 81%

The influence of salinity on toxicological effects of arsenic in digestive gland of clam Ruditapes philippinarum using metabolomics

Wu²,

Liu

et al. 2013

Chin. J. Ocean. Limnol.

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Ruditapes philippinarum , a clam that thrives in intertidal zones of various salinities, is a useful biomonitor to marine contaminants. We investigated the infl uence of dilution to 75% and 50% of normal seawater salinity (31.1) on the responses of the digestive gland of R . philippinarum to arsenic exposure (20 μg/L), using nuclear magnetic resonance (NMR)-based metabolomics. After acute arsenic exposure for 48 h, salinity-dependent differential metabolic responses were detected. In normal seawater, arsenic exposure increased the concentrations of branched-chain amino acids, and of threonine, proline, phosphocholine and adenosine, and it decreased the levels of alanine, hypotaurine, glucose, glycogen and ATP in the digestive glands. Differential changes in metabolic biomarkers observed at lower salinity (~23.3) included elevation of succinate, taurine and ATP, and depletion of branched-chain amino acids, threonine and glutamine. Unique effects of arsenic at the lowest salinity (~15.6) included down-regulation of glutamate, succinate and ADP, and up-regulation of phosphocholine. We conclude that salinity infl uences the metabolic responses of this clam to arsenic.

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“…A recent metabolomic study observed several nicotinamide metabolites to be elevated in the urine of both T2DM rodents and T2DM humans. Interestingly, these metabolites were also reported to be biomarkers for peroxisome proliferator-activated receptor ␣ activation (10,65,66). Given the clear role of peroxisome proliferator-activated receptor ␣ and its family members in fatty acid metabolism, pipecolic acid and nicotinamide metabolites as diagnostic biomarkers for T2DM in human patients should be evaluated.…”

Section: Discussionmentioning

confidence: 99%

Metabolomics Reveals Attenuation of the SLC6A20 Kidney Transporter in Nonhuman Primate and Mouse Models of Type 2 Diabetes Mellitus

Patterson

Bonzo

et al. 2011

Journal of Biological Chemistry

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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...

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Potential urinary and plasma biomarkers of peroxisome proliferation in the rat: identification ofN-methylnicotinamide andN-methyl-4-pyridone-3-carboxamide by¹H nuclear magnetic resonance and high performance liquid chromatography

Cited by 71 publications

References 29 publications

Beyond lipids, pharmacological PPARα activation has important effects on amino acid metabolism as studied in the rat

Beyond lipids, pharmacological PPARα activation has important effects on amino acid metabolism as studied in the rat

The influence of salinity on toxicological effects of arsenic in digestive gland of clam Ruditapes philippinarum using metabolomics

Metabolomics Reveals Attenuation of the SLC6A20 Kidney Transporter in Nonhuman Primate and Mouse Models of Type 2 Diabetes Mellitus

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