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Molecular Endocrinology, doi:10.1210/me.2007-0150
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Molecular Endocrinology 21 (9): 2136-2151
Copyright © 2007 by The Endocrine Society

Metabolomic and Genetic Analysis of Biomarkers for Peroxisome Proliferator-Activated Receptor {alpha} Expression and Activation

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

Laboratory of Metabolism (Y.Z., K.W.K., C.C., F.J.G.), National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892; and Institute of Pharmacology (J.R.I.), First Faculty of Medicine, Charles University, 128 00 Praha 2, Czech Republic

Address all correspondence and requests for reprints to: Frank J. Gonzalez, Laboratory of Metabolism, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892. E-mail: fjgonz{at}helix.nih.gov.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Peroxisome proliferator-activated receptor {alpha} (PPAR{alpha}) 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 PPAR{alpha} agonists, a metabolomic investigation was undertaken in wild-type and Ppar{alpha}-null mice fed for 2 wk either a regular diet or a diet containing the PPAR{alpha} 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 Ppar{alpha} (–/–) mice plus two additional discrete phenotypes for the treated and untreated Ppar{alpha} (+/+) mice. Biomarkers of PPAR{alpha} 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. PPAR{alpha} urinary biomarkers highly statistically significantly elevated by Wy-14,643 treatment included 11ß-hydroxy-3,20-dioxopregn-4-en-21-oic acid (>3700-fold), 11ß,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-ß-D-glucuronide (3-fold). PPAR{alpha} 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 PPAR{alpha} 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.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
PEROXISOME PROLIFERATOR-ACTIVATED receptor {alpha} (PPAR{alpha}) belongs to the nuclear receptor superfamily. After binding to its ligands, PPAR{alpha} forms a heterodimer with the retinoid X receptor (RXR), which then disengages corepressors and/or recruits coactivators and binds to specific direct repeat 1-type DNA elements, called peroxisome proliferator response elements (PPREs), in the promoter regions of target genes involved in lipid, glucose, and amino acid homeostasis (1, 2). In rodent models, long-term treatment with PPAR{alpha} ligands results in hepatocellular carcinomas (3, 4), whereas this phenomenon is absent in Ppar{alpha}-null mice (5). It is of great interest to understand the mechanism of PPAR{alpha}-induced liver toxicity and carcinogenesis.

A more global approach to study PPAR{alpha} and other nuclear receptors could rely on extensive analysis of the pool of small organic molecules or metabolites that are present in a biological medium, also called the "metabolome" (6). Metabolomics, also called metabonomics, is defined as the quantitative measurement of the dynamic multiparametric metabolic response of living system to pathophysiological stimuli or genetic modification (7) and has been mostly performed using methodology centered on high-field nuclear magnetic resonance spectroscopy with data analyzed by multivariate data analysis (MDA) methods such as principal components analysis (PCA) (8, 9, 10). Recent advances in mass spectrometric techniques, especially when linked to the newly introduced very high-resolution ultra-performance liquid chromatography (UPLC), have resulted in the development of robust methods for low-molecular-mass organic molecules in complex biological matrices that can also be combined with MDA to yield sets of accurate mass ions, by electrospray in both positive and negative ion modes, that describe the differences between two or more groups of samples (11). The application of PCA to urinary metabolite profiles provides an unbiased evaluation of the metabolites that characterize the difference in urine composition between two groups of animals, for example, male vs. female mice, or different strains of mice (11). Contemporary mass spectrometry methods, such as UPLC-coupled time-of-flight mass spectrometry (TOFMS), are able to detect approximately 5000 ion-retention time pairs in a single urine sample (12). PCA is able to define metabolic phenotypes and also identify which of the urinary ion-retention time pairs contributes most to the separation between two phenotypes. Because the ions are acquired by the TOFMS with a mass error of typically less than 5 ppm, it is generally possible to deduce the empirical formulae of candidate metabolites. Authentic standards, acquired by either purchase or chemical synthesis, are then used to confirm the urinary metabolites that contribute to a particular phenotype.

Metabolites produced by any of the target gene products of PPAR{alpha} are theoretical biomarkers for PPAR{alpha} activation. One candidate metabolic set arises from the tryptophan-niacin pathway that is upregulated by PPAR{alpha} ligands (13). A study using nuclear magnetic resonance-based metabolomics has reported elevated urinary excretion of 1-methylnicotinamide (MNM) and 1-methyl-4-pyridone-3-carboxamide after exposure of rats to PPAR{alpha} agonists (14, 15).

In this study, the occurrence of urinary biomarkers of Ppar{alpha} activation in the mouse is reported. To accomplish this, Ppar{alpha}+/+ and Ppar{alpha}–/– mice were treated with the prototypical PPAR{alpha} ligand Wy-14,643 ([4-chloro-6-(2,3-xylidino)-2-pyrimidinylthio] acetic acid), and urines were analyzed using UPLC-TOFMS coupled with MDA.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Phenotype of PPAR{alpha} Induction by Wy-14,643
To validate the efficacy of Wy-14,643 treatments, liver and body weights were determined after 15 d of Wy-14,643 feeding. Body weights were (mean ± SD) 20.4 ± 1.7 and 22.4 ± 0.7 g in treated and 22.8 ± 1.5 and 24.5 ± 1.1 g for the untreated +/+ and –/– mice, respectively. These data revealed a 10% decrease in body weight (P < 0.05) for the treated +/+ mice compared with either the treated –/– mice or the untreated groups. In addition, liver to body weight ratio on d 15 was 0.15, 0.043, 0.041, and 0.055 for the +/+ treated, –/– treated, +/+ untreated, and –/– untreated groups, respectively, revealing a 3-fold increase (P < 0.005) in relative liver mass for the Wy-14,643-treated +/+ mice only. Together, this phenotype is consistent with previous reports (3, 5), thus demonstrating Wy-14,643 activation of PPAR{alpha}.

MDA of Mouse Urines
UPLC-TOFMS analysis of urine coupled with MDA was used to profile urinary metabolome changes attributable to both nonactivated PPAR{alpha} (untreated +/+ vs. untreated –/–) and Wy-14,643-treated PPAR{alpha}-activated (treated +/+ vs. untreated –/–) mice. The differences between all four groups of mice were best described by PCA with four components, having a R2 value of 0.58 and a Q2 value of 0.37 (Fig. 1AGo). Data from each of the four groups of animals clustered together, showing relatively little interindividual differences. The treated and untreated –/– mouse urines clustered together, but the treated and untreated +/+ mouse urines were widely separated in component 1. Moreover, untreated +/+ and untreated –/– urines separated slightly in component 1 but widely in component 2. Accordingly, it was decided to perform PCA analysis on the two untreated groups, with a view of uncovering differences attributable to the endogenous effect of the Ppar{alpha} gene, in the absence of ligand activation. For the untreated animals alone (+/+ vs. –/–), PCA yielded two components with R2 of 0.44 and Q2 of 0.24 (Fig. 1BGo). The +/+ and –/– groups separated widely in component 1. In contrast to the Wy-14,643-treated animals, there was considerable within-group variation in component 2, which could not be explained by housing in different cages. Because of these clear group separations in the PCA scores plots, it was not necessary to use supervised multivariate analyses such as partial least-squares discriminant analysis or orthogonal projection to latent surfaces. This initial PCA analysis revealed specific metabolic phenotypes associated with the presence/absence of the Ppar{alpha} gene and/or treatment with the PPAR{alpha} ligand Wy-14,643. Having established that ligand activation of PPAR{alpha} generated unique metabolic phenotypes in +/+ and –/– mice and that untreated +/+ and –/– also displayed a different metabolic phenotype, PCA was further used to scrutinize which urinary ions were responsible for these PPAR{alpha}-specific phenotype differences.


Figure 1
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  		Fig. 1. PCA Scores Plots for Mouse Urinary Metabolomes

A, PCA scores plot of component 1 vs. component 2 for four groups of mice, wild-type (+/+) and Ppar{alpha}-null (–/–) mice, both untreated and treated with Wy-14,643 (Wy). B, PCA scores plot of component 1 vs. component 2 for two groups of mice, untreated wild-type (+/+) and Ppar{alpha}-null (–/–) mice.

 
Examination of the loadings plot for the Wy-14,643-treated animals (Fig. 2AGo) revealed ions that deviated from the cloud of ions representing the urinary metabolome. These fell broadly into three groups. First, several ions were elevated in the treated +/+ animals (toward the bottom right of Fig. 2AGo). Second, ions were discernible that were reduced in the treated +/+ animals compared with the treated –/– animals (toward the top left of Fig. 2AGo). Finally, a group of ions were apparent that were elevated in untreated +/+ mice compared with untreated –/– mice (toward the bottom left of Fig. 2AGo). In general, therefore, an increase in component 1 appears to be associated with Ppar{alpha} activation by Wy-14,643, and a decrease in component 2 appears to be associated with the presence of the Ppar{alpha} gene itself.


Figure 2
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  		Fig. 2. PCA Loadings Plots for Mouse Urinary Metabolomes

A, PCA loadings plot showing the effect of both Wy-14,643 and Ppar{alpha} on the mouse urinary metabolome. Ions 1–6 are elevated in +/+ mice relative to –/– mice after Wy-14,643 treatment. Ions 7–9 are reduced in +/+ mice relative to –/– mice after Wy-14,643 treatment. Ion 10 is representative of substances that are excreted in higher amount in untreated +/+ mice relative to untreated –/– mice. Ions correspond to the following: HDOPA, 1; DHOPA, 2; 2,8-dihydroxyquinoline-ß-D-glucuronide, 3; NMO, 4; NM, 5; hippuric acid, 6a and 6b; cinnamoylglycine, 7a and 7b; hexanoylglycine, 8; phenylpropionylglycine, 9; DHQ, 10; XA, 11 (see below). B, PCA loadings plot showing the effect of Ppar{alpha} on the mouse urinary metabolome. Ions 7a, 7b, 10, and 11 are elevated in +/+ mice compared with –/– mice. Ions 6a and 6b are reduced in +/+ mice compared with –/– mice.

 
Perusal of the loadings plot for untreated animals revealed ions that are associated with the presence and absence of the Ppar{alpha} gene (Fig. 2BGo). Specifically, ions most deviated to the right of Fig. 2BGo are associated with the presence of the Ppar{alpha} gene, whereas those to the left are associated with the absence of the gene. It is of interest to note that two ions could be identified in Fig. 2Go, both A and B, that were associated with the presence of the Ppar{alpha} gene, specifically, ions 10 and 11.

Identification of Biomarkers for PPAR{alpha} Activation
Examination of the contributions table from SIMCA-P software revealed that 6393 positive ions had been detected. The top 100 ions (50 elevated and 50 reduced by Wy-14,643 treatment) that contributed most to the separation between groups were then analyzed, and 12 empirical formulae were identified by their accurate masses. Values of mass to charge ratio (m/z) for protonated molecular ions or fragment ions (empirical formula) that were elevated in treated +/+ mice compared with treated –/– mice were 361.201 (C21H29O5), 363.216 (C21H31O5), 105.034 (C7H5O), 338.087 (C15H16NO8), 180.066 (C9H10NO3), 139.0.51 (C6H7N2O2), and 123.057 (C6H7N2O). The corresponding ions that were reduced in treated +/+ mice compared with treated –/– mice were 131.049 (C9H7O), 206.082 (C11H12NO3), 174.113 (C8H16NO3), and 208.098 (C11H14NO3). Two ions were identified that were increased in the untreated +/+ mice compared with the untreated –/– mice and were 162.054 (C9H8NO2) and 206.044 (C10H8NO4).

Biomarkers Elevated in Ppar{alpha}+/+ Mice Relative to Ppar{alpha}–/– Mice after 14 d of Wy-14,643 Treatment
Regarding the ions elevated in treated +/+ mice, the top ranking three ions plus four others were unequivocally identified, as follows and as listed in Table 1Go. 11ß-Hydroxy-3,20-dioxopregn-4-en-21-oic acid (HDOPA) (C21H29O5; MH+ = 361.202) was the top ranking ion in the urine of +/+ mice treated with Wy-14,643. This mass corresponds to both aldosterone and cortisone. These candidates were both eliminated on the basis of their retention times and tandem mass spectrometry (MSMS) fragmentation (data not shown). It was noted that the corresponding negative ion ([M-H]– = 359.187) was four times more abundant in mouse urine than the positive ion. In addition, the deprotonated molecular ion readily formed a dimer ([M2-H]– = 719.366) in negative ion mode, typical of a carboxylic acid (16). Therefore, the 20-oxo 21-oic acid derived from corticosterone, which had the same mass (see above), was synthesized. Structural identity of this biomarker was confirmed by comparison of the urinary ion with the synthetic material using UPLC-MSMS (Fig. 3AGo).


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  		Table 1. Ions Elevated in Mouse Urine after 14 d Treatment with Wy-14,643

 

Figure 3
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  		Fig. 3. UPLC-MSMS of Synthetic vs. Urinary HDOPA (A) and Synthetic vs. Urinary DHOPA (B).

 
11ß,20-Dihydroxy-3-oxopregn-4-en-21-oic acid (DHOPA) (C21H31O5; MH+ = 363.217) was clearly HDOPA plus two hydrogens. The 20-hydroxy compound had been synthesized previously (17, 18). This compound had been described as a major metabolite of corticosterone found in the liver 1 h after ip injection of corticosterone to mice (17). Thus, the chemical identity of this biomarker was establishing by synthesis of this 20-hydroxy 21-oic acid (see above) and comparison of the MSMS fragmentation patterns of the synthetic and urinary materials (Fig. 3BGo).

Hippuric acid (benzoylglycine; C9H10NO3; MH+ = 180.066 and 105.034, fragment) gave perfect matches for hippuric acid and its benzoyl cation. Comparison of retention times and MSMS fragmentation for authentic hippuric acid and the urinary compound (Fig. 4AGo) established the identity of this biomarker.


Figure 4
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  		Fig. 4. Tandem MS of Hippucuric Acid, DHQ, and DHQ Glucuronide

A, UPLC-MSMS of synthetic vs. urinary hippuric acid. Note that the protonated molecular ion (marked MH+) is unstable and absent from the spectra. B, UPLC-MSMS of synthetic vs. urinary DHQ. C, UPLC-MSMS of DHQ glucuronide in urine. The 2-O-glucuronide is shown. This biomarker may also be the 8-O-glucuronide or a mixture of both. Fragmentation with loss of 176 Da is shown.

 
2,8-Dihydroxyquinoline-ß-D-glucuronide (C15H16NO8; MH+ = 338.088) represents a common urinary finding in the mouse. To confirm the identity of this biomarker, urines were treated with ß-glucuronidase and then reanalyzed by UPLC-TOFMS. Increases in 2,8-dihydroxyquinoline (DHQ) proportional to the glucuronide were observed (data not shown), and the presence of DHQ was determined by the comparison of the MSMS fragmentation of authentic DHQ and the urinary compound (Fig. 4BGo). In addition, the MSMS of the glucuronide in urine was studied and was consistent with the proposed structure (Fig. 4CGo) because of the diagnostic loss of 176 Da for glucuronides.

The identities of nicotinamide (NM) (C6H7N2O; MH+ = 123.056), nicotinamide 1-oxide (NMO) (C6H7N2O2; MH+ = 139.051), MNM (C7H9N2O; MH+ = 137.071), and xanthurenic acid (XA) (C10H8NO4; MH+ = 206.045) were established by comparison of MSMS fragmentations of authentic standards and the urinary compounds (Fig. 5Go).


Figure 5
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  		Fig. 5. UPLC-MSMS of Synthetic vs. Urinary NM (A), NMO (B), MNM (C), and XA (D)

Note that the protonated molecular ion (marked MH+ in D) is unstable and absent from the spectra.

 
Biomarkers Reduced in Ppar{alpha}+/+ Mice Relative to Ppar{alpha}–/– Mice after 14 d of Wy-14,643 Treatment
Regarding the ions reduced in treated +/+ mice, the second ranking ion plus three others were unequivocally identified. All four ions were derived from three glycine conjugates, those of cinnamic acid [131.050+ (cinnamoyl cation fragment) and 206.082+], phenylpropionic acid (208.097+), and hexanoic acid (174.113+) (Table 2Go). All three glycine conjugates were readily confirmed by comparison of the MSMS fragmentation of authentic vs. the urinary compounds (data not shown). Both decreased and increased glycine conjugation of benzoic acid to hippuric acid has been reported in rats treated with PPAR{alpha} activator fibrate drugs (19).


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  		Table 2. Ions Decreased in Mouse Urine after 14 d Treatment with Wy-14,643

 
Biomarkers Increased in Untreated Ppar{alpha}+/+ Mice Relative to Ppar{alpha}–/– Mice
Two ions, ranking second and third in the SIMCA-P contributions table, were identified unequivocally. The first of these was unconjugated DHQ (162.056+), which has already been dealt with above and whose authentication is depicted in Fig. 4BGo. The second was XA (206.045+) (Table 3Go). The presence of this biomarker in urine was confirmed by comparison of the MSMS fragmentation of authentic compound and the urinary substance (Fig. 5Go).


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  		Table 3. Ions Elevated in Ppar{alpha}+/+ Mouse Urine Compared with Ppar{alpha}–/– Mouse Urine

 
Quantitation of Biomarkers in Urine of Wy-14,643-Fed Ppar{alpha}+/+ and Ppar{alpha}–/– Mice and Control-Fed Ppar{alpha}+/+ and Ppar{alpha}–/– Mice
All biomarkers in Tables 1–3GoGoGo were quantitated by UPLC-TOFMS using calibration curves with theophylline as an internal standard. With the exception of the two corticosteroids HDOPA and DHOPA, all data were expressed as micromoles per millimole creatinine and thus were independent of urine volume. The mean ± SD urinary excretion on d 14 after continuous feeding with a Wy-14,643 diet and control diet in both Ppar{alpha}+/+ and Ppar{alpha}–/– mice (eight per group) for HDOPA, DHOPA, and the four metabolites of the tryptophan-niacin pathway are displayed (Fig. 6Go). Because of insufficient synthetic standards of sufficient purity, proper calibration curves could not be constructed for DHOPA and HDOPA. Therefore, urinary excretion of HDOPA and DHOPA was calculated in terms of peak area of each compound relative to the theophylline internal standard area and then divided by millimoles of creatinine excreted. Whereas –/– mice treated with Wy-14,643 had undetectable HDOPA in their urine, treated +/+ mice had a value of 374 ± 109 standardized units of HDOPA in their urine. Moreover, –/– mice had 3.6 ± 1.7 normalized units of urinary DHOPA, but, in +/+ mice, this value rose to 172 ± 64. These intergenotype differences were highly statistically significant (P < 0.0001). In the untreated groups, there were no significant differences in excretion of either HDOPA or DHOPA.


Figure 6
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  		Fig. 6. Quantitation of d 14 Urinary HDOPA (black bars), DHOPA (white bars), NM, NMO, MNM, and XA in Wy-14,643-Fed Ppar{alpha}+/+ and Ppar{alpha}–/– Mice and Control Ppar{alpha}+/+ and Ppar{alpha}–/– Mice

Group differences were calculated by two-tailed unpaired Student’s t test (eight mice per group). Data are given as mean ± SEM.

 
Activation of PPAR{alpha} by Wy-14,643 caused a highly statistically significant (P = 0.0001) 5-fold increase (299 ± 110 to 1490 ± 320 µmol/mmol creatinine) in NMO excretion, a highly statistically significant (P = 0.001) greater than 2-fold increase (198 ± 112 to 453 ± 136) in NM excretion, and a statistically significant (P = 0.014) 50% increase (60.9 ± 11 to 92.9 ± 30) in MNM excretion, relative to mice receiving the control diet. There were no statistically significant differences in the excretion of these three biomarkers between untreated Ppar{alpha}+/+ and Ppar{alpha}–/– mice. In addition, activation of PPAR{alpha} by Wy-14,643 was associated with a statistically significant (P = 0.02) approximate 30% decreased excretion of XA. Interestingly, untreated +/+ mice had the highest excretion of XA, a highly statistically significantly (P = 0.0001) 2-fold elevated excretion compared with untreated –/– mice. This finding is consistent with the position of XA on the loadings plot (Fig. 2AGo).

Activation of PPAR{alpha} by dietary Wy-14,643 had a profound effect on the urinary excretion of DHQ and its glucuronide (Fig. 7Go). Not only did PPAR{alpha} activation significantly (P = 0.008) enhance excretion of the glucuronide, but the total conjugated plus unconjugated DHQ was also increased from 150 ± 150 to 392 ± 223 µmol/mmol creatinine (P = 0.04). In the untreated groups, there was a considerable difference in excretion of unconjugated DHQ between +/+ and –/– mice (P < 0.0001) that was not reflected in a compensatory difference in excretion of the glucuronide. Indeed, an enhanced excretion of free plus conjugated DHQ of 397.9 ± 196.7 was observed in +/+ mice vs. 49.6 ± 53.0 µmol/mmol creatinine for –/– mice (P = 0.0003). Thus, the wild-type (+/+) Ppar{alpha} genotype is associated with increased excretion of free plus conjugated DHQ in both Wy-14,643-treated and untreated mice. The effect of PPAR{alpha} activation by dietary Wy-14,643 was to shift the excretion to the glucuronide metabolite (Fig. 7Go).


Figure 7
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  		Fig. 7. Quantitation of d 14 Urinary DHQ, 2,8-Dihydroxyquinoline-ß-D-glucuronide, Hexanoylglycine, Hippuric Acid, Phenylpropionylglycine, and Cinnamoylglycine in Wy-14,643-Fed Ppar{alpha}+/+ and Ppar{alpha}–/– Mice and Control Ppar{alpha}+/+ and Ppar{alpha}–/– Mice

Group differences were calculated by two-tailed unpaired Student’s t test (eight mice per group). Data are given as mean ± SEM.

 
Urinary excretion of three glycine conjugates hexanoylglycine, phenylpropionylglycine, and cinnamoylglycine was significantly decreased (P < 0.0001 to 0.004) in both treated and untreated +/+ mouse groups relative to –/– mice (Fig. 7Go). Interestingly, the excretion of hippuric acid (benzoylglycine), although decreased in the untreated +/+ relative to –/– mice, displayed an increase (P < 0.0001) associated with PPAR{alpha} activation by Wy-14,643.

Metabolomic analysis of urine from Ppar{alpha} +/+ and –/– mice fed a diet containing the PPAR{alpha} ligand Wy-14,643 uncovered PPAR{alpha}-specific urinary metabolic phenotypes that were characterized by both elevated and reduced excretion of endogenous metabolites, presumably as a result of the induction of PPAR{alpha} target genes and resultant alterations in host metabolism.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
MATERIALS AND METHODS
 REFERENCES
 
This study underscores the power of metabolomics combined with transgenic mouse models in uncovering biomarkers associated with a single genotype or phenotype, in this case the Ppar{alpha}+/+ genotype and the activated PPAR{alpha} phenotype. Four groups of mice were used, Wy-14,643-treated and untreated Ppar{alpha}+/+ and Ppar{alpha}–/– mice. Clear group differences were apparent on PCA, which established that off-receptor effects of dietary Wy-14,643 treatment were minimal, because the untreated and treated Ppar{alpha}-null mice clustered together in the scores plot (Fig. 1AGo). However, a large on-receptor effect was apparent for the treated wild-type mice, with a shift of the treated +/+ cluster relative to the untreated +/+ cluster (Fig. 1AGo). A major change in the urinary metabolome was therefore expected because of PPAR{alpha} activation by dietary Wy-14,643. Interestingly, a similar difference in the scores plot was observed for the untreated Ppar{alpha} wild-type and null mice (Fig. 1BGo), suggesting the presence of an activated PPAR{alpha} phenotype in the absence of exogenous PPAR{alpha} ligand treatment. As with the treated groups, a change in the urinary metabolome attributable to the genotype difference alone could be anticipated. Examination of the loadings plots (Fig. 2Go) and analysis of the ions derived from them (Figs. 3–5GoGoGo) yielded a number of biomarkers that were associated with PPAR{alpha} activation. The most dramatic increase in urinary excretion was observed for two derivatives of corticosterone, HDOPA and DHOPA (Fig. 8Go). These appear to be highly specific biomarkers for PPAR{alpha} activation in the mouse (Fig. 6Go). The urinary excretion of DHOPA is elevated approximately 50-fold and that of HDOPA even more so, rising from undetectable (<0.1 unit/mmol creatinine) in the treated null mice to 374.3 ± 108.8 unit/mmol creatinine in the treated wild-type mice (>3700-fold). The question remains as to which target gene of PPAR{alpha} is responsible for this massively elevated synthesis and excretion of HDOPA and DHOPA. The in vivo conversion of corticosterone (Fig. 8Go, [I]) to DHOPA (Fig. 8Go, [III]) may well proceed via the aldehyde intermediate 11ß-hydroxy-3,20-dioxopregn-4-en-21-al (Fig. 8Go, [IIa]) as it does in the chemical synthesis. In fact, we demonstrated that various recombinant human cytochromes P450, and especially cytochrome P450 3A4 (CYP3A4), are able to convert corticosterone to the gem-diol form of the aldehyde (Fig. 8Go, [IIb]) (supplemental Fig. 1AGo, published as supplemental data on The Endocrine Society’s Journals Online web site at http://mend.endojournals.org). This oxidation of an alcohol to its corresponding aldehyde was not performed by hepatic alcohol dehydrogenase (supplemental Fig. 1BGo). In none of these in vitro experiments was there any evidence of the formation of DHOPA or HDOPA, as judged by MSMS comparisons, in both electrospray positive and negative ion modes, with the two urinary and synthetic corticosteroid acids. Because CYP3A4 is highly abundant in the liver (20), the conversion of corticosterone to its aldehyde presumably occurs readily, and the formation of DHOPA by isomerization of the aldehyde (Fig. 8Go) and its subsequent dehydrogenation to HDOPA are both reactions performed by as yet unidentified PPAR{alpha} target gene products. Possible candidates include aldehyde dehydrogenase type 3, lactate dehydrogenase A4 (DHOPA to HDOPA is analogous to lactate to pyruvate), 11ß-hydroxysteroid dehydrogenase I and 17ß-hydroxysteroid dehydrogenase I, or one of the many cytochromes P450 that are upregulated by PPAR{alpha} in the mouse (21). Elucidation of this falls beyond the scope of this report.


Figure 8
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  		Fig. 8. Synthetic Scheme for the Two Steroid Acids DHOPA ([III]) and HDOPA ([IV]) from Corticosterone [I] via Its 21-Aldehyde [IIa]

The aldehyde also exists in a hydrated gem-diol form [IIb].

 
The excretion in the various mouse groups of four tryptophan metabolites in the tryptophan-NM pathway was also uncovered in this study. NM (Fig. 9Go) is a catabolic product of nicotinamide adenine dinucleotide (NAD). NM was significantly elevated in wild-type compared with Ppar{alpha}-null mice. Moreover, two NM metabolites, NMO and MNM, were also both significantly elevated in Ppar{alpha}+/+ mice (Fig. 6Go). The secondary NM metabolites 1-methyl-2-pyridone-5-carboxamide (2-Py) and 1-methyl-4-pyridone-5-carboxamide (4-Py) were not determined. The major NM excretory product in all mice was NMO, representing about 70% of the NM-related metabolites in Wy-14,643-treated +/+ mice, in which it was increased 6-fold over the –/– mice. In contrast, MNM showed only a modest, but statistically significant (P = 0.014), difference between treated +/+ and –/– mice. This biomarker had been reported previously to be associated with PPAR{alpha} activation in the rat (14). The enhanced excretion of NM, NMO, and MNM was to be expected, given the critical role played by PPAR{alpha} in regulating the tryptophan-NM pathway through its down-regulation of {alpha}-amino-ß-carboxymuconate-{epsilon}-semialdehyde decarboxylase (ACMSD) (EC 4.1.1.45) (22). As Fig. 9Go shows, flux from tryptophan to NM, in particular between 3-hydroxyanthranilic acid and quinolinic acid, is influenced by the degree of leakage out of the pathway, by conversion of {alpha}-amino-ß-carboxymuconate-{epsilon}-semialdehyde (ACMS) to {alpha}-aminomuconate-{epsilon}-semialdehyde (AMS) by ACMSD. Also fitting these expectations is the observation that XA showed a modest decrease in excretion in treated +/+ mice vs. –/– mice. In contrast, however, XA excretion was significantly increased in untreated +/+ mice relative to –/– mice. This may simply reflect the complexity of the effects of PPAR{alpha} on the tryptophan-NM pathway (22, 23, 24).


Figure 9
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  		Fig. 9. The Tryptophan-NM Pathway Showing the Hepatic Conversion of the Essential Amino Acid L-Tryptophan (L-Trp) to NM and the Formation of NAD

L-Trp undergoes ring opening, leading to 3-hydroxykynurenine (3-HK), which can then either be converted to the urinary metabolite XA or to 3-hydroxyanthranilic acid (3-HA), which in turn forms ACMS. This intermediate represents a key branch point in the pathway with either the nonenzymic conversion of ACMS to quinolinic acid (QA) or decarboxylation by ACMSD (EC 4.1.1.45), which terminates the conversion of L-Trp to NAD through the formation of AMS, which is further catabolized. The NM metabolites shown are NMO, MNM, and 2-Py and 4-Py. ACMSD is a hepatic PPAR{alpha} target gene product that is negatively regulated (22 ).

 
The increased glucuronidation of DHQ in treated +/+ mice compared with all other groups may be attributable to PPAR{alpha} up-regulation of one or more UDP-glucuronosyltransferases. To our knowledge, there have been no reported studies of the glucuronidation of DHQ. UGT1A9 was reported to be a PPAR{alpha} target gene (25), and quantitative structure-activity relationships reported the glucuronidation of multiple simple and bulky phenols by UGT1A9 (26). Induction of UGT1A9 by Wy-14,643 is a likely explanation for our observation that 2,8-dihydroxyquinoline-ß-D-glucuronide is a urinary biomarker for PPAR{alpha} activation in the mouse. The formation of DHQ is probably performed by the gut microbiota. This compound has been reported to be formed from quinoline by Pseudomonas species in sewage (27, 28). Its formation by gut microbiota or by mammalian tissues has not been reported. As discussed above, the excretion of free plus conjugated DHQ is considerably greater in both treated and untreated +/+ mice compared with their respective –/– counterparts. This suggests that the Ppar{alpha}+/+ genotype alone is influencing the biosynthesis of DHQ. It may be speculated that this is evidence for an effect of a host nuclear receptor on gut floral metabolism, by an as yet unidentified mechanism.

Finally, the excretory pattern of four glycine conjugates, one aliphatic and of fatty acid origin (hexanoylglycine) and three aromatic (benzoyl-, phenylpropionyl-, and cinnamoyl-glycines), was influenced by PPAR{alpha} activation. The observations may be rationalized in terms of the known effects of PPAR{alpha} on mitochondrial fatty acid ß-oxidation (21), whereby up-regulated ß-oxidation might be expected to reduce the pool of coenzyme A (CoA) available for mitochondrial glycine conjugation. For example, because medium-chain acyl-CoA dehydrogenase is up-regulated by PPAR{alpha} (21), hexanoyl-CoA would be expected to be ß-oxidized rapidly, with little conjugation to hexanoylglycine taking place. The findings in Fig. 7Go appear to support this view. In addition, the phenylpropionic acid derivatives phenylpropionic acid itself and cinnamic acid may also undergo enhanced ß-oxidation, yielding benzoic acid, which would then be conjugated with glycine to hippuric acid and excreted. Again, this is one explanation for the link between PPAR{alpha} and the findings in Fig. 7Go. Alternatively, the gut microbiota may also play a role. A reciprocal relationship between hippuric acid excretion and the excretion of chlorogenic acid metabolites, attributed to differences in gut floral metabolism, has been reported as comprising two distinct phenotypes in rats (29). The two phenotypes, designated "high hippuric acid" and "high chlorogenic acid," differed 5-fold in hippuric acid excretion. The low hippuric acid excreting "high chlorogenic acid" phenotype was reported to revert to the "high hippuric acid" phenotype when rats of both phenotypes were housed in the same room. If such phenotypes also exist in the mouse, they may be PPAR{alpha} dependent. It should be noted that the untreated Ppar{alpha}+/+ genotype is a phenotypically low excretor of hippuric acid compared with the –/– phenotype (P < 0.0001) (Fig. 7Go). Because mammals excrete relatively little unchanged benzoic acid (30), low and high excretors of hippuric acid are presumably low and high producers of benzoic acid, respectively.

From the application of UPLC-TOFMS-based metabolomics to the study of transgenic mice, a number of elevated urinary biomarkers for PPAR{alpha} activation were uncovered in this study. These include HDOPA, DHOPA, 2,8-dihydroxyquinoline-ß-D-glucuronide, NM, NMO, and MNM. Several other attenuated urinary biomarkers were found, those whose excretion declined in concert with PPAR{alpha} activation, and included XA, hexanoylglycine, phenylpropionylglycine, and cinnamoylglycine. This pattern of an altered urinary metabolome that reflects the phenotype of PPAR{alpha} activation may serve as a noninvasive evaluation of PPAR{alpha} activation in patients receiving drugs that are PPAR{alpha} ligands and as a means of determining in vivo and noninvasively the pharmacological efficacy of novel drugs in clinical trials that are known or suspected to possess PPAR{alpha} ligand activity.

A summary of the induction of PPAR{alpha} target genes in the mouse as detected by urinary metabolomics is shown in Fig. 10Go. Two contrasting induction mechanisms are shown, both of which are reflected in the urinary metabolic phenotypes that have been defined here. First, ligand-activated PPAR{alpha} has been reported to reduce hepatic hepatocyte nuclear factor 4{alpha} (HNF4{alpha}) levels and proposed as the mechanism by which PPAR{alpha} reduces transcription of ACMSD, a key gene in the tryptophan-NM pathway and de novo NAD synthesis (22). Accordingly, our observation that the Ppar{alpha}+/+ metabolic phenotype includes elevated urinary excretion of the NAD metabolites NM, MNO, and NMN can be interpreted on the basis of the known effects of PPAR{alpha} on the enzyme ACMSD. In contrast, when the PPAR{alpha}-RXR heterodimer binds to the PPRE of target genes, this can be detected in the PPAR{alpha}+/+ urinary metabolic phenotype as increased synthesis and urinary excretion of metabolites of the affected enzymes. The massive urinary elevation (>3700-fold) of the corticosteroid acid HDOPA in treated +/+ mice relative to –/– mice, together with the 50-fold increase in excretion of its precursor DHOPA, can be interpreted as attributable to the induction by PPAR{alpha} of a dehydrogenase enzyme, presumably a 20-hydroxysteroid dehydrogenase (Fig. 10Go). In turn, the DHOPA precursor of HDOPA must arise by isomerization of the product of corticosterone oxidation by cytochrome P450, likely by a CYP3A enzyme in mice because CYP3A4 can perform this reaction (supplemental Fig. 1Go). This isomerization is unlikely to be a spontaneous reaction, because DHOPA excretion is so elevated in the PPAR{alpha}+/+ metabolic phenotype. Our observations cannot be explained by the up-regulation of Cyp3a transcription, because these genes are unlikely to be PPAR{alpha} target genes (21). The power of metabolomics in combination with genetically modified mice, as shown in Fig. 10Go, is that it may uncover new pathways of endogenous metabolism and potential novel nuclear receptor target genes.


Figure 10
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  		Fig. 10. Mechanistic Representation of the Proposed Role of Ligand-Activated PPAR{alpha} in the Generation of Urinary Biomarkers Observed in Ppar{alpha}+/+ Mice Relative to Ppar{alpha}–/– Mice

The reduced activity of ACMSD-mediated conversion of ACMS to AMS occurs because of reduced levels of HNF4{alpha} brought about by ligand-activated PPAR{alpha}. This reduced ACMS metabolism, in turn, leads to the spontaneous ring closure of ACMS to quinolinic acid (see Fig. 9Go) and further metabolism to NAD, which is detected as enhanced NAD urinary metabolites, NM, NMO, and NMN. In contrast, ligand-activated PPAR{alpha}-RXR heterodimer binds to the PPRE of an as yet unidentified target gene, leading to increased synthesis of HDOPA from DHOPA, presumably by a hydroxysteroid dehydrogenase (HSD) enzyme. DHOPA is itself synthesized from corticosterone by CYP3A4 (supplemental Fig. 1Go), thus suggesting that a mouse CYP3A performs this reaction and a putative isomerase.

 

   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
REFERENCES
 
Chemicals
Hexanoylglycine and phenylpropionylglycine were obtained from the Metabolic Laboratory, Vrije Universiteit Medical Center (Amsterdam, The Netherlands). Corticosterone was purchased from Steraloids (Newport, RI). NM, NMO, MNM, hippuric acid, cinnamoylglycine, titanium (III) chloride, copper (II) acetate, aldosterone, cortisone, corticosterone, theophylline, and ß-glucuronidase powder (type H-1 from Helix pomatia) were purchased from Sigma (St. Louis, MO). DHQ was provided by the Developmental Therapeutics Program, National Cancer Institute (Frederick, MD). HPLC-grade solvents (acetonitrile, ethanol, and water) were purchased from Fisher Scientific (Hampton, NH).

Synthesis of DHOPA and HDOPA
DHOPA was synthesized according to previously described methods (17, 18). In brief, a solution of 120 mg copper (II) acetate in 60 ml methanol was added to a solution of 500 mg corticosterone in the same solvent (40 ml). The mixture was stirred at room temperature for 10 min, air was bubbled through the mixture for an additional 60 min, and then the methanol was removed by evaporation. The corresponding 21-aldehyde was obtained in the organic phase by extraction using a mixture of aqueous sodium sulfate (8%) and ethyl acetate. After evaporation of the ethyl acetate, the crude product was subjected to chemical rearrangement with 0.18 M sodium hydroxide. The resultant DHOPA was extracted into 1 vol ethyl acetate after the reaction mixture was adjusted to pH 2.0 with 5 M HCl. The yield was 30%. HDOPA was obtained by oxidation of DHOPA with alkaline silver nitrate (31, 32), with a yield of 20%. The reaction scheme is shown in Fig. 8Go.

Titanium (III) Chloride Reduction
TiCl3 was used to reduce N-oxide derivatives as described recently (12). Twenty-microliter ice-cold urine samples were added to 20 µl ice-cold TiCl3 (or 5 M HCl as a negative control), and the solution vortexed for 10 sec. The reaction mixture was agitated at room temperature for 1 h, and 40 µl saturated sodium bicarbonate and 20 µl water were added to the reaction to yield a final pH of 3.0. After brief centrifugation, the solution was analyzed by UPLC-TOFMS.

Animals and Treatments
C57BL/6N male Ppar{alpha}-null mice (33) were used in this study; the corresponding 5- to 6-wk-old wild-type mice were purchased from Charles River Laboratories (Frederick, MD). Mice were housed three to five animals per cage (six to eight mice per group), maintained under a standard 12-h light, 12-h dark cycle with water and chow provided ad libitum. Handling was in accordance with an animal study protocol approved by the National Cancer Institute Animal Care and Use Committee. Mice were put on a rodent grain base diet (Bioserv, Frenchtown, NJ) for 2 wk. Animals in control groups were on the same diet for another 2 wk, whereas treatment groups were changed to a 0.1% Wy-14,643 diet (Bioserv).

Urine Collections
Mice were placed in glass metabolic cages (Jencons, Leighton Buzzard, UK) for 24 h on d 10 and d 12 of Wy-14,643 treatment to acclimate to the cages. On d 11 and 13, they were returned to their home cages. On d 14, mice were placed again in glass metabolic cages, and urine samples were collected for 24 h and stored at –80 C until analysis. Mice were killed on d 15, and livers and serum were collected and stored at –80 C.

UPLC-TOFMS Analyses
Urine samples were diluted with 4 vol of 50% aqueous acetonitrile and centrifuged at 18,000 x g to remove particulates and proteins. Urine samples (5µl/injection) were subjected to chromatography on a 50 x 2.1 mm ACQUITY 1.7 µm BEH C18 column (Waters Corp., Milford, MA) using an ACQUITY UPLC system (Waters Corporation) with a gradient mobile phase comprising 0.1% formic acid (A) and acetonitrile containing 0.1% formic acid (B). A 0.5 ml/min flow rate was maintained in a 10-min run. The gradient comprised 100% A for 0.5 min, increasing to 100% B over the next 7.5 min and returning to 100% A in 2 min. The eluent was introduced directly into the mass spectrometer by electrospray. Mass spectrometry was performed on a Waters Q-TOF Premier operating in positive ion mode. Source temperature and desolvation temperature were set at 120 C and 350 C, respectively. Nitrogen was used as both cone gas (50 liters/h) and desolvation gas (600 liters/h), and argon as collision gas. The capillary voltage and the cone voltage were set to 3000 and 30 V, respectively. Sulfamethoxine was used as the lock mass (m/z of 311.0814) for accurate mass calibration and introduced using the LockSpray interface at 60–70 µl/min and a concentration of 0.5 ng/µl in 50% aqueous acetonitrile. In mass spectrometry scanning, data were acquired in the centroid mode from 100 to 850 m/z. For MSMS fragmentation of target ions, collision energies ranging from 15 to 35 V were applied.

MDA of Urinary Metabolite Markers
Centroided and integrated mass spectrometric data were processed by MarkerLynx mass spectrometry software (Waters Corporation) to generate a multivariate data matrix. The retention time window was set between 0.1 and 6.5 min, and mass window was set between 100 and 850 with a mass tolerance at 0.05. Ions that were obviously derived from Wy-14,643, specifically of m/z of 324.057 (Wy-14,643 parent compound), 340.052 (putative hydroxylated Wy-14,643), and 354.032 (putative Wy-14,643 carboxy metabolite) were excluded from the data matrix. In addition, MetaboLynx software (Waters Corp.) was used to generate a table of ions that derived from theoretical Wy-14,643 metabolites, e.g. putative glucuronides and sulfates of hydroxylated and dihydroxylated Wy-14,643, and these were also deleted from the data matrix. The data matrix was further analyzed by SIMCA-P+ 11 software (Umetrics, Kinnelon, NJ). PCA was conducted after the data were transformed by Pareto scaling, in which the importance of the low-concentration metabolites was increased, without noise amplification. Identification of the potential biomarkers of PPAR{alpha} activation was performed by analyzing the corresponding loading plots and contribution lists generated by MarkerLynx.

Structure Elucidation of the Urinary Markers
The molecular formulae were calculated from the accurate masses using MassLynx with a mass tolerance of 10 ppm. Biologically plausible empirical formulae were used to search multiple chemical databases to reveal potential candidate biomarkers. When authentic standards were available, confirmation of identity was sought by comparison of UPLC retention times and MSMS spectra. In the case of NMO, additional confirmation of the identity of this biomarker in mouse urine was obtained by reduction of urines with TiCl3, which is specific for N-oxides (see above).

Quantification of Urinary Metabolites
MetaboLynx and QuantLynx software were applied to quantify the amounts of urinary metabolites from their peak areas. In the case in which authentic standards were available, specifically NM (MH+ = 123.056 m/z), MNM (M+ = 137.072 m/z), and NMO (MH+ = 139.051 m/z), calibration curves were constructed from 0.1 to 5.0 µM using theophylline (3.125 µM; MH+ = 181.073 m/z) as internal standard. In the case of XA (MH+ = 206.0453) and DHQ (MH+ = 162.0555), calibration curves were constructed from 5–25 µM, and, for hexanoylglycine (MH+ = 174.1130), hippuric acid (MH+ = 180.0661), phenylpropionylglycine (MH+ = 208.0974), and cinnamoylglycine (MH+ = 206.0817), the calibration range was 10–100 µM. Creatinine concentration (0.1 to 5.0 µM; MH+ = 114.067 m/z) was also calculated from the mass spectrometry data using theophylline as internal standard, as above. The retention time window set at 0.25–0.40 min depending on the size of the peak, and mass window set was at 0.010 atomic mass units. Absolute peak areas were used to calculate peak area ratios (analyte/theophylline). All calibration curves were linear from 0.1 to 5.0 µM for each analyte as follows (r and P values, respectively): NM, 0.95 and <0.0001; MNM, 0.92 and <0.0001; NMO, 0.98 and <0.0001; XA, 0.96 and <0.0001; DHQ, 0.91 and 0.0003; hippuric acid, 0.99 and <0.0001; hexanoylglycine, 0.99 and <0.0001; phenylpropionylglycine, 0.99 and <0.0001; cinnamoylglycine, 0.97 and <0.0001; and creatinine, 0.97 and <0.0001. Limits of sensitivity were as follows (micromolar): creatinine, 0.1; NM, 0.1; MNM, 0.05; and NMO, 0.01; XA, 5; DHQ, 5; hexanoylglycine, 10; hippuric acid, 10; phenylpropionylglycine, 10; and cinnamoylglycine, 10. The relative insensitivity of the method for the four glycine conjugates is a reflection of their relatively poor ionization in the electrospray positive ion mode. Concentrations of 2,8-dihydroxyquinoline-ß-D-glucuronide were estimated from the increase in DHQ (MH+ = 162.0555) after deconjugation with ß-glucuronidase for 18 h at pH 5.0. In all cases, the ion corresponding to the glucuronide (MH+ = 338.0876) disappeared after hydrolysis. Concentration of each analyte in mouse urine (dilutions from 5- to 300-fold) was determined from these calibration curves and expressed as micromoles per millimoles creatinine.


   FOOTNOTES
 
This work was supported by the National Cancer Institute Intramural Research Program and in part by National Institutes of Health National Institute of Allergy and Infectious Diseases Grant U19 AI067773-02. J.R.I. was supported by the United States Smokeless Tobacco Company under a grant for collaborative research.

Disclosure Statement: The authors have nothing to disclose.

First Published Online June 5, 2007

Abbreviations: ACMS, {alpha}-Amino-ß-carboxymuconate-{epsilon}-semialdehyde; ACMSD, {alpha}-amino-ß-carboxymuconate-{epsilon}-semialdehyde decarboxylase; AMS, {alpha}-aminomuconate-{epsilon}-semialdehyde; CoA, coenzyme A; CYP3A4, cytochrome P450 3A4; DHOPA, 11ß,20-dihydroxy-3-oxopregn-4-en-21-oic acid; DHQ, 2,8-dihydroxyquinoline; HDOPA, 11ß-hydroxy-3,20-dioxopregn-4-en-21-oic acid; HNF4{alpha}, hepatocyte nuclear factor 4{alpha}; m/z, mass to charge ratio; MDA, multivariate data analysis; MNM, 1-methylnicotinamide; MSMS, tandem mass spectrometry; NAD, nicotinamide adenine dinucleotide; NM, nicotinamide; NMO, nicotinamide 1-oxide; PCA, principal components analysis; PPAR, peroxisome proliferator-activated receptor; PPRE, peroxisome proliferator response element; 2-Py, 1-methyl-2-pyridone-5-carboxamide; 4-Py, 1-methyl-4-pyridone-5-carboxamide; RXR, retinoid X receptor; TOFMS, time-of-flight mass spectrometry; UPLC, ultra-performance liquid chromatography; XA, xanthurenic acid.

Received for publication March 19, 2007. Accepted for publication May 30, 2007.


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Endocrinology Endocrine Reviews J. Clin. End. & Metab.
Molecular Endocrinology Recent Prog. Horm. Res. All Endocrine Journals