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

Yueying Zhen, Kristopher W. Krausz, Chi Chen, Jeffrey R. Idle, Frank J. Gonzalez

Research output: Contribution to journalArticlepeer-review

68 Scopus citations

Abstract

Peroxisome proliferator-activated receptor α (PPARα) 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 PPARα agonists, a metabolomic investigation was undertaken in wild-type and Pparα-null mice fed for 2 wk either a regular diet or a diet containing the PPARα 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 Pparα (-/-) mice plus two additional discrete phenotypes for the treated and untreated Pparα (+/+) mice. Biomarkers of PPARα 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. PPARα urinary biomarkers highly statistically significantly elevated by Wy-14,643 treatment included 11β-hydroxy-3,20- dioxopregn-4-en-21-oic acid (>3700-fold), 11β,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-β-D-glucuronide (3-fold). PPARα 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 PPARα 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.

Original languageEnglish (US)
Pages (from-to)2136-2151
Number of pages16
JournalMolecular Endocrinology
Volume21
Issue number9
DOIs
StatePublished - Sep 2007

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