Metabolomic and genetic analysis of biomarkers for peroxisome proliferator-activated receptor alpha expression and activation

过氧化物酶体增殖物激活受体α表达和激活的生物标志物的代谢组学和遗传学分析

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Abstract

Peroxisome proliferator-activated receptor alpha (PPARalpha) is a nuclear receptor with manifold effects on intermediary metabolism. To define a set of urinary biomarkers that could be used to determine the efficacy of PPARalpha agonists, a metabolomic investigation was undertaken in wild-type and Pparalpha-null mice fed for 2 wk either a regular diet or a diet containing the PPARalpha ligand Wy-14,643 ([4-chloro-6-(2,3-xylidino)-2-pyrimidinylthio] acetic acid), and their urine was analyzed by ultra-performance liquid chromatography coupled with time-of-flight mass spectrometry. Principal components analysis of 6393 accurate mass positive ions revealed clustering as a single phenotype of the treated and untreated Pparalpha (-/-) mice plus two additional discrete phenotypes for the treated and untreated Pparalpha (+/+) mice. Biomarkers of PPARalpha activation were identified from their accurate masses and confirmed by tandem mass spectrometry of authentic compounds. Biomarkers were quantitated from raw chromatographic data using appropriate calibration curves. PPARalpha urinary biomarkers highly statistically significantly elevated by Wy-14,643 treatment included 11beta-hydroxy-3,20-dioxopregn-4-en-21-oic acid (>3700-fold), 11beta,20-dihydroxy-3-oxopregn-4-en-21-oic acid (50-fold), nicotinamide (>2-fold), nicotinamide 1-oxide (5-fold), 1-methylnicotinamide (1.5-fold), hippuric acid (2-fold), and 2,8-dihydroxyquinoline-beta-d-glucuronide (3-fold). PPARalpha urinary biomarkers highly statistically significantly attenuated by Wy-14,643 treatment included xanthurenic acid (1.3-fold), hexanoylglycine (20-fold), phenylpropionylglycine (4-fold), and cinnamoylglycine (9-fold). These biomarkers arise from PPARalpha effects on tryptophan, corticosterone, and fatty acid metabolism and on glucuronidation. This study underscores the power of mass spectrometry-based metabolomics combined with genetically modified mice in the definition of monogenic metabolic phenotypes.

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