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Endocrinology and Metabolism |
1 Division of Metabolic Diseases, Department of General Pediatrics, University Children’s Hospital Heidelberg, Heidelberg, Germany.
2 Laboratory of Metabolism, Department of General Pediatrics and Adolescent Medicine, University Children’s Hospital Freiburg, Freiburg, Germany.
3 University of California, San Diego, La Jolla, CA.
aAddress correspondence to this author at: Division of Metabolic Diseases, Department of General Pediatrics, University Children’s Hospital Heidelberg, Im Neuenheimer Feld 150, D-69120 Heidelberg, Germany. Fax 49-6221-564069; e-mail Susen.Hartmann{at}med.uni-heidelberg.de.
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Abstract |
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Methods: We used reversed-phase HPLC electrospray ionization tandem mass spectrometry to investigate 24 metabolites of purine and pyrimidine metabolism in urine samples from healthy persons and from patients with confirmed diagnoses of inherited metabolic disorders. Urine samples were filtered and diluted to a creatinine concentration of 0.5 mmol/L. Stable-isotope–labeled internal standards were used for quantification. The metabolites were analyzed by multiple-reaction monitoring in positive and negative ionization modes.
Results: Total time of analysis was 20 min. Recovery (n = 8) of a compound after addition of a known concentration was 85%–133%. The mean intraday variation (n = 10) was 12%. The interday variation (n = 7) was 
17%. Age-related reference intervals were established for each compound. Analysis of patient urine samples revealed major differences in tandem mass spectrometry profiles compared with those of control samples. Twelve deficiencies were reliably detected: hypoxanthine guanine phosphoribosyl transferase, xanthine dehydrogenase, purine nucleoside phosphorylase, adenylosuccinate lyase, uridine monophosphate synthase, adenosine deaminase, adenine phosphoribosyl transferase, molybdenum cofactor, thymidine phosphorylase, dihydropyrimidine dehydrogenase, dihydropyrimidinase, and ß-ureidopropionase.
Conclusion: This method enables reliable detection of 13 defects in purine and pyrimidine metabolism in a single analytical run.
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Introduction |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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Pathways involved in 9 heritable metabolic disorders of purine metabolism and 7 heritable metabolic disorders of pyrimidine metabolism are depicted in Fig. 1 of the Data Supplement that accompanies the online version of this article at http:www.clinchem.org/content/vol52/issue6. Clinical manifestations of inherited defects of purine metabolism vary considerably, even among patients in the same family (2). The central nervous, renal, and hematologic systems are the most affected. Insoluble metabolites such as uric acid, xanthine, and 2,8-dihydroxyadenine cause urinary tract calculi and arthritis. The uric acid concentration is a useful diagnostic marker for deficiencies of phosphoribosyl pyrophosphate synthetase (PRPPS), 1 hypoxanthine guanine phosphoribosyl transferase (HGPRT), purine nucleoside phosphorylase (PNP), xanthine dehydrogenase (XDH), and molybdenum cofactor (2). Clinical features of pyrimidine degradation disorders are seizures and mental retardation (3). The key biochemical manifestation of all of these disorders is a change in the urinary excretion of purines or pyrimidines.
The method presented allows complete assessment of the urinary excretion of all relevant purines and pyrimidines, permitting the diagnosis of each of the disorders of purine and pyrimidine metabolism.
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Materials and Methods |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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internal standard mixture
Stable-isotope–labeled reference compounds used as internal standards were purchased from Cambridge Isotope Laboratories. Unfortunately, such compounds were not available for all metabolites studied; therefore, each internal standard was selected based on its similarity to the corresponding metabolite in structure, retention time, and fragmentation pattern. To make stock solutions, we dissolved each component in 1-propanol–water (1:1 by volume).
An internal standard mixture consisting of 500 µmol/L each of [8-13C]adenine, [1'-13C]adenosine, [1,3-15N2]orotic acid, [15N]uracil, d4-thymine, d6-dihydrothymine, and 13C-labeled N-carbamyl-ß-alanine and 1000 µmol/L d4-dihydrouracil was prepared with eluent A of the HPLC method.
urine samples
The control population consisted of 77 children aging from 2 months to 18 years. The urine specimens were collected in our hospital specifically for this study from completely healthy and nonsymptomatic volunteers. We investigated patient samples collected previously for laboratory tests and stored as positive controls in our hospital; the samples were from the following patients: a 6-year-old male patient with adenine phosphoribosyl transferase (APRT) deficiency; a 5-month-old male patient with HGPRT deficiency; a 1-month-old female patient with XDH deficiency; a 6-year-old male patient with PNP deficiency; an 8-month-old patient with adenosine deaminase (ADA) deficiency; a 5-year-old male patient with uridine monophosphate synthase (UMPS) deficiency; a 6-year-old male patient with adenylosuccinate lyase (ASL) deficiency; a 16-year-old male patient with thymidine phosphorylase (TP) deficiency; a 4-year-old male patient with ß-ureidopropionase (UP) deficiency; a 1-year-old patient with dihydropyrimidinase (DHP) deficiency; a 5-year-old male patient with dihydropyrimidine dehydrogenase (DPD) deficiency; and a 3-year-old male patient with molybdenum cofactor deficiency.
The sample collection for this study was approved by the ethics committee (ethics application number 071/2005; University Children’s Hospital Heidelberg, Germany). Urine samples were stored at –20 °C until analysis. Urinary creatinine concentrations were determined by the alkaline-creatinine-picrate method (5). Before analysis, urine samples were diluted to 0.5 mmol/L creatinine with eluent A and filtered with a centrifuge filter (Millipore) with a pore size of 0.1 µm. We added 20 µL of internal standard mixture to 180-µL aliquots of urine or diluted urine and then injected 20 µL of the prepared urine into an HPLC system with detection by electrospray ionization tandem mass spectrometry (ESI MS/MS).
hplc-ms/ms
The HPLC system consisted of a Rheos 2000 quaternary pump and a vacuum degasser connected to a CTC pal autosampler. A reversed-phase column [Aqua C18 Minibore; 250 x 2.0 mm (i.d.); 5 µm particle size; Phenomenex] protected by a guard column of the same material was used for chromatography. Column temperature was maintained at 23 °C. For separation of the compounds, the following eluents were used: eluent A consisted of 0.05 mol/L acetic acid, adjusted to pH 4 with 250 g/L NH4OH and adjusted again to pH 2.8 with undiluted formic acid; eluent B was a mixture of solvent A and methanol (1:1 by volume). A flow rate of 100 µL/min was applied. The following linear elution gradient was used: 0–2 min, 100% A; 2–10 min, 100% A to 0% A; 10–11 min, 0% A; 11–11.5 min, 0% to 100% A. Between runs, the system was reequilibrated with 100% A for 8.5 min. HPLC ESI MS/MS analysis required 20 min.
A Quattro Ultima tandem mass spectrometer (Micromass) was used. The purines (except 2-deoxyadenosine), orotic acid, pseudouridine, uridine, 2-deoxyuridine, 5-hydroxymethyluracil, and thymidine were ionized in negative ionization mode. The pyrimidine degradation products and 2-deoxyadenosine were positively ionized. Nitrogen served as desolvation, nebulizing, and cone gas, and argon was used as collision gas. Cell pressure was 0.153 Pa. The optimum source temperature was 100 °C. Compounds were analyzed in multiple-reaction-monitoring experiments, in which preselected ion pairs were entered. Ion pairs, cone voltages, and collision energies are summarized in Table 1
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analytical validation
The specific tandem mass spectrometric conditions for each compound were optimized by use of a 100 µmol/L stock solution of each metabolite. A flow rate of 10 µL/min was chosen.
Linearities and detection limits were determined by injection of urine samples enriched with different metabolite concentrations. Linearity curves for analyte peak area/internal standard peak area plotted vs standard concentration were generated. The slopes and intercepts of the linearity curves were used for analyte quantification. The detection limit was defined as the lowest concentration that gave a signal-to-noise ratio of 3.
To establish the intraday variation, we analyzed a blank urine sample plus 3 urine samples enriched with low (10 µmol/L), medium (50 µmol/L), and high concentrations (100 µmol/L) of the metabolites 10 times within 1 day. For uric acid, higher concentrations (200 and 400 µmol/L) were chosen because urinary concentrations are higher. For succinyladenosine and 2,8-dihydroxyadenine, lower concentrations (7.5 and 35 µmol/L and 35 and 70 µmol/L, respectively) were selected. For determination of interday variation, urine samples with the same concentration as for the evaluation of the intraday variation were analyzed in duplicate on 7 separate days.
We evaluated recoveries by analyzing 8 different urine samples in duplicate before and after enrichment with 25 and 75 µmol/L of purine and pyrimidine metabolites. We determined the recoveries of succinyladenosine and 2,8-dihydroxyadenenine by measuring 4 different urine samples enriched with these analytes at 15 and 35 µmol/L.
We investigated the influence of urine pH by adjusting the pH to between 3 and 9 in 4 separate urine samples. Before analysis, all 4 samples were enriched with identical concentrations of purines and pyrimidines. The resulting concentrations were compared with each other and also with the added concentrations.
To estimate reference intervals, we assayed urine samples from 77 healthy children from 2 months to 18 years of age. Age- and sex-related concentration dependence was investigated by a 5-step procedure. First, analysis of covariance (ANCOVA) was performed for each detectable metabolite as the dependent variable with sex as an independent variable and age as a covariate. Results revealed no primary effect for sex and no interaction for age by sex for any of the metabolites. Significant age effects were observed for 7 of 22 metabolites (see Table 5
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Visual partitioning of the raw data plotted by age was performed for those metabolites showing a significant result (step 2; see cutoff age in Table 5
). Next (step 3) we tested the log(x + 1)-transformed distributions below and above the cutoff ages, using the algorithm published by Lahti et al. (6). The log(x + 1) transformation was used to handle the problem of log-transformation of zero values for certain metabolites. Decision for partitioning was based on R values as the ratio of the SDs of the larger by the smaller age distribution and the differences D (measured in SD units) between the age distributions at their lower (DLower limit) and upper (DUpper limit) tails. This procedure corroborated the visual age partitioning for all metabolites. In step 4, we calculated the 95% confidence intervals of the means according to the modified Cox algorithm (7). Finally (step 5), we calculated the reference intervals for all metabolites by back-transforming the logarithmic confidence intervals to the original scale. Readers should be aware that the back-transformed variables are geometric means (as estimators of the median) and the multiplicative SD (instead of the additive SD) (8). Shown in Table 5
are the means, SDs, and reference intervals. All statistical calculations were performed with the "R software environment for statistical computing" (9).
To compare chromatograms obtained for patient urine samples with those from healthy individuals, we analyzed urine samples from patients in whom a metabolic disorder had been confirmed previously. To mimic urine of patients with PRPPS superactivity, urines were enriched with hypoxanthine (100–120 mmol/mol creatinine), uric acid (>1900 mmol/mol creatinine), and xanthine (100–120 mmol/mol creatinine) (10).
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Results |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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. Signal intensities and retention times of the purines and pyrimidines are presented in Fig. 2 of the online Data Supplement for negatively ionized compounds and in Fig. 3 of the online Data Supplement for positively ionized metabolites. Each metabolite displayed specific ion pairs and characteristic retention times (Table 1
). Optimal peak shapes were achieved for all analytes except for dihydrouracil and N-carbamyl-ß-alanine, which were characterized by broader and split peaks. Uracil had less response than the other metabolites. Interferences between the metabolites in this method were overcome by HPLC separation and elution at different times. Adenosine, uridine, and thymidine produced ions that corresponded to the ion pairs of adenine, uracil, and thymine, respectively. The HPLC column separated the metabolites in the urine samples from salt, which would cause quenching of metabolite signals in the ion source of the tandem mass spectrometer.
Ion pairs for creatinine and its internal standard were also included in the method to ensure correct dilution of the sample (data not shown). This ratio was checked before quantification.
linearity and detection limits
The ranges of linearity and the detection limits for each metabolite and its corresponding internal standard are presented in Table 2
. Eight internal standards were used for the quantification of 24 purines and pyrimidines. Several purines and pyrimidines were quantified up to 600 mmol/mol creatinine (300 µmol/L). Uridine and 2-deoxyuridine were quantified up to 400 mmol/mol creatinine (200 µmol/L). 2-Deoxyadenosine, 2,8-dihydroxyadenine, and N-carbamyl-ß-amino-isobutyric acid were quantifiable up to 200 mmol/mol creatinine (100 µmol/L) and succinyladenosine up to 140 mmol/mol creatinine (70 µmol/L). Uric acid was quantified from 200 to 1600 mmol/mol creatinine (100–800 µmol/L). For sample metabolite concentrations higher than the upper limit of linearity, we diluted the sample to a concentration within the linear range and reanalyzed.
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For xanthine, adenosine, 2,8-dihydroxyadenine, uracil, thymine, dihydrouracil, dihydrothymine, N-carbamyl-ß-aminoisobutyric acid, N-carbamyl-ß-alanine, uridine, and pseudouridine, the detection limit was between 1 and 10 µmol/L. For all other metabolites, the detection limit was <0.2 µmol/L. Patient urine samples with decreased concentrations of these metabolites (e.g., uric acid in XDH, molybdenum cofactor, or PNP deficiency) were successfully identified with this method.
precision
The intraday variations for the various metabolites are presented in Table 3
. The mean CV for urine samples with 50 µmol/L added standard solution (200 µmol/L for uric acid, 35 µmol/L for succinyladenosine and 2,8-dihydroxyadenine) was 12%. Mean recovery was 106%. In addition to the data shown in Table 3
, intraday CVs were 7%–20% for urines enriched with 10 µmol/L each metabolite except for hypoxanthine, uracil, and pseudouridine, which had CVs of 31%, 28%, and 27%, respectively. The mean recovery was 104%. CVs were 6%–24% for urines enriched with 100 µmol/L of each metabolite. Dihydrouracil was an exception; its CV was higher, at 42%. Dihydrouracil eluted in a split peak, making integration difficult, and showed variable background, which led to an increased CV value. Mean recovery for this concentration was 102%.
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Data for the interday variation are presented in Table 3
. The interday CVs were 17% for urines enriched with 50 µmol/L for all metabolites except uric acid (200 µmol/L), succinyladenosine (30 µmol/L), and 2,8-dihydroxyadenine (35 µmol/L). The only higher CV was 25% for 2,8-dihydroxyadenine. Recoveries were 92%–125%. In addition, urines enriched with lower concentrations (10 µmol/L) had CVs of 8%–31%. The mean recovery for these less concentrated urines was 101%. The CVs and recoveries for urine samples enriched with 100 µmol/L of each metabolite were 3%–12% and 95%–109%, respectively.
analytical recovery
We analyzed 8 different urine samples before and after addition of known metabolite concentrations. The mean recoveries and CVs are listed in Table 4
. Recoveries ranged from 85% to 123% with the exceptions of 2-deoxyinosine, 2-deoxyadenosine, and thymidine, for which recoveries were 133%, 128%, and 128%, respectively. The CVs were 9%–24% for all metabolites except for hypoxanthine, thymine, and thymidine, which had CVs of 34%, 28%, and 33%, respectively. We also determined the recoveries for lower concentrations (25 and 150 µmol/L for uric acid). The mean recovery was 111%, and the mean CV was 19%.
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carryover
We investigated carryover by assaying an unenriched urine sample after assaying urine samples with added metabolites. No carryover was detected.
To investigate the influence of pH, we analyzed 4 enriched urine samples with different pH values in the range of 3–9. No differences in concentrations or peak shapes were detected.
reference intervals and control ranges
The reference intervals for all of the metabolites are listed in Table 5
. For xanthine, hypoxanthine, inosine, uracil, N-carbamyl-ß-alanine, N-carbamyl-ß-aminoisobutyric acid, and pseudouridine, we found that the reference intervals were age dependent, whereas the other metabolites showed no age dependence. For 2-deoxyinosine, adenosine, 2-deoxyadenosine, guanosine, 2-deoxyguanosine, succinyladenosine, orotic acid, thymine, dihydrouracil, dihydrothymine, uridine, 2-deoxyuridine, and 5-hydroxymethyluracil, sample concentrations were below the lower limits of quantification, as were the concentrations of inosine and N-carbamyl-ß-aminoisobutyric acid for children older than 1 year and N-carbamyl-ß-alanine for children older than 4 years of age. Upper reference limits were defined by the maximum measured concentration in the first age group for inosine, N-carbamyl-ß-alanine, and N-carbamyl-ß-aminoisobutyric acid. The reference sample concentrations of these 3 metabolites were partly below the lower limits of quantification, and no mean could be calculated. 2,8-Dihydroxyadenine and thymidine were not detectable in urine from healthy persons.
samples from patients with confirmed deficiencies
Urine samples from patients with confirmed diagnoses [deficiencies of APRT, ADA, PNP, UMPS, ASL, TP, UP, DHP, DPD, XDH, molybdenum cofactor, and HGPRT] were analyzed. The chromatograms (Fig. 1
) illustrated major differences from those of urine specimens from healthy individuals. In each case, the correct diagnosis was readily apparent. The urine sample from the patient with APRT deficiency showed a peak corresponding to 2,8-dihydroxyadenine and contained some unidentified compounds that did not interfere with the recognition and quantification of 2,8-dihydroxyadenine. There were also unidentified peaks in the chromatogram of adenosine in the urine sample from the patient with ADA deficiency. In the sample from the patient with DHP deficiency, there were unidentifiable peaks in the chromatograms of dihydrouracil and dihydrothymine.
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Discussion |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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Existing methods for the analysis of purines and pyrimidines are gas chromatography–MS, which involves time-consuming sample preparation (11)(12), and reversed-phase HPLC coupled with ultraviolet detection, which requires an analytical run time of 
30 min and is more susceptible to disruptive elements in the urinary matrix. A proton nuclear magnetic resonance (1H-NMR) spectrometric method can be used to measure many compounds of purine and pyrimidine metabolism (13), but it has a major disadvantage in that it fails to detect uric acid and 2,8-dihydroxyadenine, which are very useful markers for the diagnosis of APRT deficiency, XDH deficiency, molybdenum cofactor deficiency, PRPPS superactivity, and HGPRT deficiency. Capillary electrophoresis can also be used to measure many analytes, but it requires time-consuming sample preparation (14).
MS/MS is a robust clinical laboratory technique in which cleaning and maintenance procedures between analyses are reduced. The applied Z-spray reduces contamination in the tandem mass spectrometer; therefore, less cleaning is required. Higher sample throughput is also possible. A method is available that uses atmospheric pressure chemical ionization MS/MS (15) with ion-exchange purification and an evaporation step as sample preparation, making the method very time-consuming. It also does not include any pyrimidine degradation products.
Three HPLC ESI MS/MS methods have been described for which sample preparation is simple (16)(17)(18), but to date, our method is the only one that provides quantification of purines, pyrimidines, and pyrimidine degradation products and requires minimum sample preparation while enabling complete analysis of relevant purine and pyrimidine metabolites in 1 analytical run. An additional advantage over previous methods is the inclusion of uric acid and 2,8-dihydroxyadenine because hyper- and hypouricemia are important in establishing diagnoses of 5 different disorders of purine metabolism (2).
Because of its polar endcapping, the Aqua HPLC column used for separation of metabolites retains basic compounds more effectively than conventional C18 columns. The combination of positive and negative ionization enables analysis of purines and pyrimidines in 1 analytical run. Uracil and thymine are also negatively ionizable (16), but in our experience the signal intensities are much higher with positively charged parent ions. No interferences of purines and pyrimidines were encountered, whereas with a previously reported method (16), dihydropyrimidines and N-carbamyl compounds could not be measured without affecting the measurement of other metabolites of the purine and pyrimidine pathways. We also did not observe any interference of 5,6-dihydrouridine with 5,6-dihydrouracil, as described previously (19). With our method, no spontaneous fragmentation of 5,6-dihydrouridine in the ion source was identified (see Fig. 4 in the online Data Supplement).
In our method, the HPLC column was necessary to separate the metabolites from unidentifiable peaks. Every metabolite was analyzed with its own specific ion pair, only adenosine, uridine, and thymidine also showed the same ion pairs as adenine, uracil, and thymine because of spontaneous fragmentation in the ion source.
The linearity ranges apply for concentrations within the pertinent reference intervals as well as pathologic concentration ranges of 2–600 mmol/mol creatinine for purines and 10–600 mmol/mol creatinine for pyrimidines. Dihydrouracil is quantifiable at 100–600 mmol/mol creatinine. The lower quantification limit of 100 mmol/mol creatinine is acceptable because concentrations in patients with DHP deficiency are usually 150–630 mmol/mol creatinine (10). The method also permits the detection of decreases in uric acid and pseudouridine concentrations.
Succinyl-5-amino-4-imidazole carboxamide riboside (SAICAR) and succinyladenosine are the 2 metabolites associated with adenylosuccinate lyase deficiency (20). Succinyladenosine was readily detectable with this method, but SAICAR was not ionizable or became instable in the ion source. SAICAR can be detected by the modified Bratton–Marshall test (21). Succinyladenosine concentrations are higher in the milder form of the disease (20).
5-Amino-4-imidazolecarboxamide ribosiduria is detectable by a combination of the modified Bratton–Marshall test and our new approach. Succinyladenosine is also excreted in concentrations that are increased but lower than those found in ASL-deficient patients (22).
In conclusion, our method allows rapid, specific, and reliable screening for defects in the purine and pyrimidine pathways. This method can be used to correctly diagnose deficiencies of APRT, ADA, PNP, UMPS, ASL, TP, DPD, DHP, UP, XDH, molybdenum cofactor, PRPPS, and HGPRT.
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Acknowledgments |
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Footnotes |
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References |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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The following articles in journals at HighWire Press have cited this article:
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  T. M. Annesley Methanol-Associated Matrix Effects in Electrospray Ionization Tandem Mass Spectrometry Clin. Chem., October 1, 2007; 53(10): 1827 - 1834. [Abstract] [Full Text] [PDF]
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