Large-Scale Human Metabolic Phenotyping andMolecular Epidemiological Studies via 1H NMRSpectroscopy of Urine: Investigation of BoratePreservation

Leon M. Smith,† Anthony D. Maher,†,‡ Elizabeth J. Want,† Paul Elliott,§ Jeremiah Stamler,|

Geoffrey E. Hawkes,⊥ Elaine Holmes,† John C. Lindon,† and Jeremy K. Nicholson*,†

Department of Biomolecular Medicine, Faculty of Medicine, Imperial College London, South Kensington, London, SW72AZ, U.K., Department of Epidemiology & Public Health, Faculty of Medicine, Imperial College London, St Mary’sCampus, Norfolk Place, London, W2 1PG, U.K., Department of Preventive Medicine, Feinberg School of Medicine,Northwestern University, Chicago, IL, and School of Biological and Chemical Sciences, Queen Mary and WestfieldCollege, University of London, Mile End Road, London E1 4NS, U.K.

Borate is an antibacterial preservative widely used inclinical and large-scale epidemiological studies involvingurine sample analysis. Since it readily forms covalentadducts and reversible complexes with hydroxyl andcarboxylate groups, the effects of borate preservation in1H NMR-spectroscopy-based metabolic profiling ofhuman urine samples have been assessed. Effects ofvarious concentrations of borate (range 0-30 mM) on1H NMR spectra of urine were observed at sequentialtime points over a 12 month period. Consistent withknown borate chemistry, the principal alterations inthe 1H resonance metabolite patterns were observedfor compounds such as mannitol, citrate, and r-hy-droxyisobutyrate and confirmed by ESI-MS analysis.These included line-broadening, T1 and T2 relaxation,and chemical shift changes consistent with complexformation and chemical exchange processes. To furtherinvestigate complexation behavior in the urinary me-tabolite profiles, a new tool for visualization of multi-component relaxation variations in which the spectrawere color-coded according to the T1 and T2 protonrelaxation times respectively (T1 or T2 ordered projec-tion spectroscopy, TOPSY) was also developed andapplied. Addition of borate caused a general decreasein 1H T1 values, consistent with nonspecific effectssuch as solution viscosity changes. Minor changes inproton T2 relaxation rates were observed for the moststrongly complexing metabolites. From a molecularphenotyping and epidemiologic viewpoint, typical in-terpersonal biological variation was shown to be vastlygreater than any variation introduced by the boratecomplexation, which had a negligible effect on themetabolic mapping and classification of samples. Whilecaution is indicated in the assignment of biomarkersignals where metabolites have diol groupings or wherethere are adjacent hydroxyl and carboxylate functions,it is concluded that borate preservation is “fit-for-purpose” for 1H NMR-based epidemiological studies,

since the essential biochemical classification featuresof the samples are robustly maintained.

Metabolic profiling of biofluids is now widely accepted as a toolfor identifying biomarkers in disease diagnosis and toxicology,1-4

and the application of spectroscopic methods, based on eitherNMR spectroscopy or mass spectrometry, is now well-validatedfor metabolic profiling of animal studies and for small-scale humanclinical studies.5-7

Understanding the variation in metabolic phenotypes is ofimportance in molecular epidemiology studies on diverse humanpopulations.8-10 The development of the concept of the metabo-lome-wide association studies (MWAS), involving the broad,nonselective analysis and statistical characterization of metabolic

* To whom correspondence should be addressed. Phone: +44(0) 20 7594-3195. E-mail: j.nicholson@imperial.ac.uk.

† Imperial College London.‡ Current address: Prince of Wales Medical Research Institute, Barker St,

Randwick, NSW 2031, Australia.§ Imperial College London, St Mary’s Campus.| Northwestern University.⊥ University of London.

(1) Coen, M.; Holmes, E.; Lindon, J. C.; Nicholson, J. K. Chem. Res. Toxicol.2008, 21, 9–27.

(2) Nicholson, J. K.; Connelly, J.; Lindon, J. C.; Holmes, E. Nat. Rev. DrugDiscovery 2002, 1, 153–161.

(3) Ala-Korpela, M. Clin. Chem. Lab. Med. 2008, 46, 27–42.(4) Tukiainen, T.; Tynkkynen, T.; Makinen, V. P.; Jylanki, P.; Kangas, A.;

Hokkanen, J.; Vehtari, A.; Grohn, O.; Hallikainen, M.; Soininen, H.; Kivipelto,M.; Groop, P. H.; Kaski, K.; Laatikainen, R.; Soininen, P.; Pirttila, T.; Ala-Korpela, M. Biochem. Biophys. Res. Commun. 2008, 375, 356–361.

(5) Beckonert, O.; Keun, H. C.; Ebbels, T. M. D.; Bundy, J.; Holmes, E.; Lindon,J. C.; Nicholson, J. K. Nature Protocols 2007, 2, 1–12.

(6) Gowda, G. A. N.; Zhang, S.; Gu, H.; Asiago, V.; Shanaiah, N.; Raftery, D.Exp. Rev. Mol. Diagn. 2008, 8, 617–633.

(7) Gika, H. G.; MacPherson, E.; Theodoridis, G. A.; Wilson, I. D. J. Chromatogr.B 2008, 871, 299–305.

(8) Holmes, E.; Wilson, I. D.; Nicholson, J. K. Cell 2008, 134, 714–717.(9) Sabatti, C.; Service, S. K.; Hartikainen, A. L.; Pouta, A.; Ripatti, S.; Brodsky,

J.; Jones, C. G.; Zaitlen, N. A.; Varilo, T.; Kaakinen, M.; Sovio, U.; Ruokonen,A.; Laitinen, J.; Jakkula, E.; Coin, L.; Hoggart, C.; Collins, A.; Turunen, H.;Gabriel, S.; Elliot, P.; McCarthy, M. I.; Daly, M. J.; Jarvelin, M. R.; Freimer,N. B.; Peltonen, L. Nat. Genet. 2009, 41, 35–46.

(10) Yan, B.; Jiye, A.; Wang, G.; Lu, H.; Huang, X.; Liu, Y.; Zha, W.; Hao, H.;Zhang, Y.; Liu, L.; Gu, S.; Huang, Q.; Zheng, Y.; Su, J. J. Appl. Physiol. 2009,106, 531–538.

Anal. Chem. 2009, 81, 4847–4856

10.1021/ac9004875 CCC: $40.75 2009 American Chemical Society 4847Analytical Chemistry, Vol. 81, No. 12, June 15, 2009Published on Web 05/19/2009

phenotypes in relation to disease outcomes and risk factors inepidemiologic studies provides a framework for generating test-able physiological hypotheses.11,12 However, the analytical andmodeling challenges involved in metabolic phenotyping of samplesfrom large-scale human population studies are greater than thosetypically found in standard clinical or toxicological studies. Thereis also huge potential for the retrospective analysis of storedsamples collected in historically important epidemiological studiesby 1H NMR spectroscopy and other analytical methods, suchas mass spectrometry, thus providing a rich source formetabolic exploration of human phenotypic variation andchanges through time.25

To extract the maximum amount of biological information fromNMR spectroscopic data sets and to avoid classification errors, itis essential to understand, minimize, and control sources of bothanalytical and biochemical variation. This is increasingly importantas advances in analytical sensitivity through the use of cryogenicprobes13 and high-throughput by means of flow injection14 arecontributing to the feasible use of NMR spectroscopy in large-scale studies, as are new methods in data processing andmultivariate statistical analysis.15-17

Several studies have investigated the sources and degree ofbiological and analytical variation in NMR-based metabonomicstudies, including sample storage temperature/time,18-20 diurnalvariation,21 dietary intake,22,23 and gender differences.24 Addition-ally, biological stability and analytical reproducibility are key issuesfor population screening studies, where samples are collected,stored, and analyzed over many months or even years. Recentstudies have assessed the stability of human urine and plasmasamples using both 1H NMR spectroscopy26- and GC-MS27-

derived metabolite profiles, which appear to be largely stableup to 36 h without freezing. However, it is normal to addantibacterial agents to field collected samples that are not frozenimmediately. Both borate and azide have been widely used aspreservatives for urine, as they are highly effective as antimicrobialagents and easy to use in the field for epidemiological studies.28-30

Of these two commonly used preservatives, borate is preferred, sinceit is much less toxic and reactive than azide, which has also beenreported to accelerate the hydrolysis of esterified metabolites.31

However, borate is reactive toward diols (particularly vicinal) andcompounds with adjacent hydroxyl and carboxylate functional groups,such as are found in many common metabolites, including carbo-hydrates, polyols, alditols, and hydroxylated fatty acids. Indeed, thecapacity for borate to bind to vicinal diols has been widelyexploited analytically in the production of phenyl-boronatesorbents and phases that can be used to extract and isolatesuitable diols, including sugars and drug glucuronides.32

Borate in aqueous solution acts as a Lewis acid, since it existsmainly as the fully hydrated B(OH)4

- ion, [B(OH)3 + H2O TB(OH)4

- + H+]. Borate can form complexes with alcohols(ROH) to yield neutral esters, such as B(OR)3, as shown inScheme 1.33,34 The ion [B(OH)4]-(aq) also readily forms anionic1:1 and 1:2 complexes with carbohydrates and most polyolspossessing 1,2 substitution (Scheme 2)35,36 and 1,3 substitution(Scheme 3),35,37 and molecules containing dicarboxylic acids anddiketones may also form complexes.36,38 These complexationreactions are readily reversible, and a number of measurements

(11) Holmes, E.; Loo, R. L.; Stamler, J.; Bictash, M.; Yap, I. K.; Chan, Q.; Ebbels,T.; De Iorio, M.; Brown, I. J.; Veselkov, K. A.; Daviglus, M. L.; Kesteloot,H.; Ueshima, H.; Zhao, L.; Nicholson, J. K.; Elliott, P. Nature 2008, 453,396–400.

(12) Nicholson, J. K.; Holmes, E.; Elliott, P. J. Proteome Res. 2008, 7, 3637–3638.

(13) Keun, H. C.; Beckonert, O.; Griffin, J. L.; Richter, C.; Moskau, D.; Lindon,J. C.; Nicholson, J. K. Anal. Chem. 2002, 74, 4588–4593.

(14) Spraul, M.; Hoffmann, M.; Ackermann, M.; Nicholls, A. W.; Damment, S. J.;Haselden, J. N.; Shockcor, J. P.; Nicholson, J. K.; Lindon, J. C. Anal.Commun. 1997, 34, 339–341.

(15) Cloarec, O.; Dumas, M. E.; Craig, A.; Barton, R. H.; Trygg, J.; Hudson, J.;Blancher, C.; Gauguier, D.; Lindon, J. C.; Holmes, E.; Nicholson, J. K. Anal.Chem. 2005, 77, 1282–1289.

(16) Bylesjo, M.; Eriksson, D.; Kusano, M.; Moritz, T.; Trygg, J. Plant J. 2007,52, 1181–1191.

(17) Trygg, J.; Holmes, E.; Lundstedt, T. J. Proteome Res. 2007, 6, 469–479.(18) Lauridsen, M.; Hansen, S. H.; Jaroszewski, J. W.; Cornett, C. Anal. Chem.

2007, 79, 1181–1186.(19) Teahan, O.; Gamble, S.; Holmes, E.; Waxman, J.; Nicholson, J. K.; Bevan,

C.; Keun, H. C. Anal. Chem. 2006, 78, 4307–4318.(20) Maher, A. D.; Zirah, S. F.; Holmes, E.; Nicholson, J. K. Anal. Chem. 2007,

79, 5204–11.(21) Bollard, M. E.; Stanley, E. G.; Lindon, J. C.; Nicholson, J. K.; Holmes, E.

NMR Biomed. 2005, 18, 143–162.(22) Lenz, E. M.; Bright, J.; Wilson, I. D.; Hughes, A.; Morrisson, J.; Lindberg,

H.; Lockton, A. J. Pharm. Biomed. Anal. 2004, 36, 841–849.(23) Stella, C.; Beckwith-Hall, B.; Cloarec, O.; Holmes, E.; Lindon, J. C.; Powell,

J.; van der Ouderaa, F.; Bingham, S.; Cross, A. J.; Nicholson, J. K. J. ProteomeRes. 2006, 5, 2780–2788.

(24) Kochhar, S.; Jacobs, D. M.; Ramadan, Z.; Berruex, F.; Fuerholz, A.; Fay,L. B. Anal. Biochem. 2006, 352, 274–281.

(25) Dumas, M. E.; Maibaum, E. C.; Teague, C.; Ueshima, H.; Zhou, B.; Lindon,J. C.; Nicholson, J. K.; Stamler, J.; Elliott, P.; Chan, Q.; Holmes, E. Anal.Chem. 2006, 78, 2199–2208.

(26) Barton, R. H. B.; Nicholson, J. K.; Elliott, P.; Holmes, E. Int. J. Epidemiol.2008, 37, i31–i40.

(27) Dunn, W. B.; Broadhurst, D.; Ellis, D. I.; Brown, M.; Halsall, A.; O’Hagan,S.; Spasic, I.; Tseng, A.; Kell, D. B. Int. J. Epidemiol. 2008, 37, i23–i30.

(28) Porter, I. A.; Brodie, J. Br. Med. J. 1969, 2, 353–355.(29) Lum, K. T.; Meers, P. D. J. Infect. 1989, 18, 51–58.(30) Gillespie, T.; Fewster, J.; Masterton, R. G. J. Clin. Pathol. 1999, 52, 95–

98.(31) Zaitsu, K.; Miki, A.; Katagi, M.; Tsuchihashi, H. Forensic Sci. Int. 2008,

174, 189–196.(32) Tugnait, M.; Ghauri, F. Y. K.; Wilson, I. D.; Nicholson, J. K. J. Pharm.

Biomed. Anal. 1991, 9, 895–899.(33) Knoeck, J.; Taylor, J. P. Anal. Chem. 1969, 41, 1730–1734.(34) Magnusson, L. B. J. Inorg. Nucl. Chem. 1971, 33, 3602–3604.(35) Ackloo, S. Z.; Burgers, P. C.; McCarry, B. E.; Terlouw, J. K. Rapid Commun.

Mass Spectrom. 1999, 13, 2406–2415.(36) Friedman, S.; Pizer, R. J. Am. Chem. Soc. 1975, 97, 6059–6062.(37) Cox, P. J. Talanta 2000, 51, 205.(38) Pesetsky, B.; Eldred, N. R. Tetrahedron 1969, 25, 4137–4145.

Scheme 1

Scheme 2

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of equilibrium constants have been published, including throughthe use of 11B NMR spectroscopy.39 The equilibrium constantsand stoichiometry of the complexed species are also highlypH-dependent, and mass spectrometry has also been used tosuccessfully characterize borate/diol complexes.35 While dataexist on complexes of borate in various solvents,40,41 multipleborate complexes with a range of metabolites have not been well-characterized, especially in terms of the kinetics and moleculardynamics of ligand exchange, although this is not a primarypurpose of our study. In this study, we have investigated theconsequences of borate addition on the 1H NMR spectral profilesof urinary metabolites, in terms of effects on proton chemicalshifts and T1 and T2 relaxation times across a range of borateconcentrations and specimen storage times. This involved theuse of both model solutions and complete urine samples. Directinfusion electrospray mass spectrometry (ESI-MS) was alsoused to confirm the formation and stoichiometry of boratecomplexes using standard solutions. The main aim was toevaluate possible influences of borate complexation on sampleclassification error in metabonomic studies and on potentialconsequent biomarker misassignment and hence to assess theextent to which borate preservation of epidemiological urinesamples is “fit-for-purpose” for large-scale human metabonom-ics and molecular phenotyping investigations.

METHODSMaterials. All chemicals were obtained from Sigma (St. Louis,

MO) except D2O (99.9%), which was from Goss ScientificInstruments Ltd. (Essex, U.K.).

Collection and Preparation of Quality-Control Samples.Ten aliquots were prepared from a 24 h human urine from aCaucasian male containing variable amounts of borate (0, 3.07,6.15, 9.22, 12.29, 16.90, 21.51, 24.58, 27.66, and 30.73 mM) to mimicpossible variation of boric acid concentration in specimens fromepidemiological studies. The highest concentration was deter-mined by the lowest urinary excretion volume (24 h) in bothINTERMAP and INTERSALT studies and the highest number ofcontainers used. Prior to analysis, 300 µL of urine was mixedwith 200 µL of buffer [0.2 M Na2HPO4, 1 mM 3-(trimethylsilyl)-2,2,3,3-d4-propionic acid (TSP), 10% (v/v) D2O, pH 7.4] andtransferred into 5 mm NMR tubes. Samples were thawedand analyzed after 0, 1, 2, 7, 14, 28, 91, 182, and 364 days ofstorage at -40 °C.

1H NMR Spectroscopy. Standard 1D 1H NMR spectra wereacquired at 300 K on either a Bruker DRX400 spectrometer

equipped with a 5 mm SEI probe operating at 400.13 MHz, aBruker Avance-II spectrometer equipped with a 5 mm TXIprobe operating at 600.22 MHz, or a Bruker Avance-IIIspectrometer equipped with a 5 mm SEI probe operating at800.32 MHz. Each spectrum was acquired using a standardwater peak presaturation pulse sequence of the formd1-90x-t1-90-tm-90x-acquire FID, where t1 is 3 µs, withselective irradiation of the water resonance during the recycledelay (d1) and mixing time (tm). A total of 64 scans was acquiredat a spectral width of 20 ppm (12 kHz at 600 MHz observation).The mixing time was 100 ms, with an acquisition time of 2.6 sand a recycle delay of 2 s. Prior to Fourier transformation, thefree induction decays were multiplied by an exponentialfunction, corresponding to a line broadening factor of 1 Hz,and zero-filled to 128k data points. Spectra were referenced tothe chemical shift of TSP (taken to be δ 0.00). Standard one-dimensional NMR spectra were also measured on modelsolutions, prepared as 1:1 metabolite:borate ratio (10 mM each),at 1H observation frequencies of 400, 600, and 800 MHz. Thesethree observation frequencies were used in order to maximizethe opportunity to observe the chemical shift changes andchemical exchange effects of any borate complexation. Inaddition, 600 MHz 1H NMR spectra have been measured on asubset (n ) 200) of human urine samples collected from theChicago arm of the study as part of the INTERSALT epide-miologic study, using the same pulse sequence and parametersas given above.25

Data Processing and Statistical Analysis. Prior to principalcomponents analysis (PCA), spectra were segmented into 0.04ppm regions, and the total peak integral was calculated withineach segment (with the segments containing the δ 4.5-5.0 regionremoved to eliminate artifacts associated with varying watersuppression) and normalized to total intensity. PCA models wereconstructed using SIMCA-P+ Version 10.5 (Umetrics, Sweden).This simplified approach using segmented integral data was usedbecause the aim of the analysis was to assess the effect of borateon PCA mapping positions and not to evaluate the spectra in termsof potential biochemical biomarkers.

Measurement of T1 and T2 Relaxation Times. The quality-control sample was used to measure apparent T1 values for allresonances simultaneously using the standard inversion re-covery pulse sequence of the form d1-180x-τ-90x-acquireFID, where d1 is a delay for relaxation (set to 10 times thelongest estimated T1) and τ is a variable T1 relaxation delay,taking values between 0.001 and 60 s. After a series of spectrawere acquired with increasing values of τ, the apparent T1 wasestimated by nonlinear regression of the intensity of each datapoint to the equation, Mz(τ) ) Mz(∞)[1 - 2 exp(-τ/T1) + c],where Mz denotes the intensity value and c is a constant. T2

values were measured using the pulse sequence d1-(τ/2-180x-τ/2)n-acquire FID, where τ was fixed at 400 µs, andn took values of 20-1920 in steps of 100, followed by nonlinearregression to the equation Mz(t) ) Mz(0) exp(-τ/T2).

Method for Constructing TOPSY Plots. Here, a newvisualization tool called T1 (or T2)-ordered projection spectros-copy (TOPSY) is introduced to aid interpretation of relaxationtime changes across multiple compounds in complex spectra.TOPSY is the projection of relaxation time parameters, calcu-

(39) Isjhii, T.; Ono, H. Carbohydr. Res. 1999, 321, 257–260.(40) Bachelier, N.; Verchere, J.-F. Polyhedron 1995, 14, 2009–2017.(41) Tyman, J. H. P.; Mehet, S. K. Chem. Phys. Lipids 2003, 126, 177–199.

Scheme 3

4849Analytical Chemistry, Vol. 81, No. 12, June 15, 2009

lated at each data point in an NMR spectrum and visualizedaccording to a color scale, onto the 1D spectrum. Followingacquisition of the series of NMR spectra, the stepwise processfor constructing TOPSY plots using Matlab (Mathworks,Natick, MA) was as follows:1 Plot the aligned NMR data matrix, X, and normalize such

that all spectra have the same average value for noise.2 Select a column vector vpeak in X known to correspond to

a metabolite resonance intensity in the spectra thatchanges in intensity as a function of the time parameterin the pulse program.

3 Compute the correlation matrix, Cpeak, between X and vpeak

using the equation Cpeak ) (n - 1)-1vpeakTX, and remove

all columns in X in which the square of the correlationcoefficient is below a given threshold. This speeds up thecalculation by removing parts of the spectral noise.

4 For longitudinal and transverse relaxation, respectively,fit each remaining column vector in X to the appropriateequations above and solve for T1 and T2. This generatesa list of T1 or T2 values (vector r) for each part per millionvalue corresponding to a spectral peak.

5 Use a suitable RGB color display function to plot the fullyrelaxed spectrum colored with values taken from r.

Direct Infusion ESI-MS Analysis. The following solutionswere analyzed (all at 10 mM): mannitol, citrate, methylmalonate,2-hydroxybutyrate, and borate, plus each standard compound at10 mM with 10 mM borate. Samples were made up in high-gradewater and infused directly into a Q-TOF Premier (Waters Micro-mass, Manchester, UK) at a flow-rate of 20 µL/min, using a 250µL Hamilton syringe connected to a syringe pump. Data werecollected using the centroid mode in both positive and negativeion mode using “V-Optics” over 5 min for each sample, scanninga mass range of 50-1000 m/z. Scan time was 1 s with an interscandelay of 0.02 s. MS conditions were as follows: capillary voltage,3200 V in positive mode and 2400 V in negative mode; samplingcone voltage, 35 V; extraction cone voltage, 5 V; desolvation gasflow, 450 L/h; cone gas flow, 0 L/h; source temperature, 120 °C;and desolvation temperature, 350 °C. The instrument was operatedwith leucine enkephalin employed as the lock-spray (Waters Corp.,Milford, MA) solution at a concentration of 200 pg/µL, infusedinto the instrument at 20 µL/min, with scans to average set tothree.

RESULTS1H NMR spectra from urine specimens stored for 24 h at

room temperature supplemented with 0 and 30.73 mM borateare shown in Figure 1, parts A and C, respectively. Visualexamination of the spectral profiles revealed that the spectra wereremarkably similar but that some minor differences could beobserved in the spectral regions δ 3.4-4.1 and 1.1-1.4. Forexample, the R-hydroxyisobutyrate methyl singlet resonance atδ 1.36 with no borate present (Figure 1A, inset, labeled 1) appearsas two singlets in the same urine sample after addition of 30.73mM borate (Figure 1B, inset labeled 1). Thus, it appears thatR-hydroxyisobutyrate exists as both the free substance and theborate complex in slow exchange. A similar behavior is observedfor the methylmalonate methyl doublet resonance at δ 1.25 (inset,labeled 2). This suggests that the sample contains a mixture of

the free metabolite and borate-complexed metabolite in slowexchange on the NMR time scale. Although not visible in Figure1 because of the complexity of the spectra, when the spectra wereexpanded, changes in the appearance of the peaks assigned tocitrate and mannitol were also visible.

Given the complexity of 1H NMR spectra of urine, the regionsof the spectra where the citrate and mannitol peaks appear werealso investigated using model solutions and a range of NMRobservation frequencies (1H observation at 400, 600, and 800MHz). The results are summarized in Figure 2, where the left-hand column shows spectra at 400 MHz, the center column at600 MHz, and the right-hand column at 800 MHz. These threeobservation frequencies were used in an attempt to maximize thevisualization of effects due to any differences in exchange ratesbetween the metabolite and the borate.

The NMR peaks for citrate comprise a standard AB pattern atall frequencies (as seen in Figure 2A-C), where the CH2 protonsare nonequivalent. On complexation with borate (Figure2D-F), the exchange between free metabolite and the boratecomplex is slow on the NMR time scale, and separate peaks wereobserved for the two species at all observation frequencies,although this is best visualized at 800 MHz, where the chemicalshift difference is greatest. Only the high-frequency componentof the AB pattern is significantly affected. The situation formannitol complexation is slightly different, and the peaks observedfor free mannitol are given in Figure 2G-I. On complexation withborate, the peak pattern is essentially unchanged, and the peaksare merely broadened at all observation frequencies (Figure2J-L). This suggests that the exchange is intermediate on theNMRtimescaleandapparently faster thanthat for theborate-citratecomplex. This could arise because either the chemical shiftdifferences between free and bound forms are smaller or theequilibrium constant is lower, such that the exchange appearsfaster on the NMR time scale and line broadening results.Alternatively, fast exchange could result from a lowering of theactivation energy.

The possible stoichiometry of the citrate- and mannitol-boratecomplexes was investigated further using mass spectrometry.Direct infusion ESI analysis of a solution of 10 mM citrate plus10 mM boric acid gave distinct peaks in negative ion mode atm/z 191.12, 390.25, and 391.24 (Figure 3A). Through comparisonwith the citrate standard alone, these were deduced to correspondto the [M - H]- ion of citrate (m/z 191.0) and a borate-citratecomplex comprising two citrate and one borate ion. Specifically,m/z 390.25 and 391.24 coincide with the mass of citrate-[10B]-citrate and citrate-[11B]-citrate, while a smaller peak atm/z 392.25 is citrate-[11B]-citrate with one 13C atom. The relativeisotopic abundance of boron [10B]:[11B] is 20:80, and the distinctiveisotope pattern of boron can be seen in the mass spectra, alsoaiding identification. This was also seen with a solution of 10 mMmannitol plus 10 mM borate, where a peak corresponding to freemannitol was observed at m/z 181.08 and a borate-mannitolcomplex comprising two mannitol molecules plus one boratemolecule at m/z 370.16 (mannitol-[10B]-mannitol) and m/z371.16 (mannitol-[11B]-mannitol) (Figure 3B). The smaller peakat m/z 372.16 is mannitol-[11B]-mannitol with one 13C atom.Finally, R-hydroxyisobutyrate (R-HIBA) also formed a complex

4850 Analytical Chemistry, Vol. 81, No. 12, June 15, 2009

with borate, again 2:1 R-HIBA:borate (Figure 3C). This gave riseto ions at m/z 103.06 (free R-HIBA) and the complex with peaks atm/z 214.14 (R-HIBA-[10B]-R-HIBA) and m/z 215.13 (R-HIBA-[11B]-3-HIBA) (Figure 3C). The smaller peak at m/z 216.15is R-HIBA-[11B]-R-HIBA with one 13C atom. This stoichiometryis likely to be the most common formed during the ESI process,where analytes are concentrated during ionization, so it isexpected that there are other stoichiometries present in loweramounts. However, based on the borate concentrations usedin this study, it appears that the urinary complexes observedby 1H NMR spectroscopy were most likely to have 1:2 borate:metabolite stoichiometry; although lower abundance speciesmay also be present, they do not appear to contributesignificantly to the NMR spectra.

Effects of Borate Complexation on Observed T1 and T2

Relaxation Times. Although in the above examples the interac-tion of borate with specific metabolites had an effect on chemicalshift and coupling patterns, it is conceivable that for othermetabolites the effects of borate interaction might be more subtle.For example, modification of relaxation parameters would not benoticeable on a single NMR spectrum but would influence therelative intensity of a given resonance when acquired understandard conditions. To visualize the potentially more subtle effectsof borate complexation across the whole biofluid spectrumand between spectra, a new method for depicting variations inT1 and T2 relaxation times, namely, TOPSY, has been devel-oped, and this was applied to the urine specimens containingthree concentrations of borate (0, 3.07, and 30.73 mM) (Figure

Figure 1. Typical 1H NMR spectra of control human urine samples containing (A) no borate; (B) expansion of the region between δ 1.1 and1.4 from A; (C) the same sample with added 30.73 mM borate; (D) expansion of the region between δ 1.1 and 1.4 from C. Peaks annotated “1”and “2” correspond to R-hydroxyisobutyric acid and methylmalonic acid, respectively, either free (in A and B) or in complex with borate (in Cand D).

4851Analytical Chemistry, Vol. 81, No. 12, June 15, 2009

4A-C for T1OPSY and D-F for T2OPSY). 1H NMR spectra wereacquired at 600 MHz using the inversion-recovery pulse se-quence for T1 relaxation measurements and the CPMG pulsesequence for T2 relaxation measurements. T1 and T2 relaxationtimes for the various proton nuclei were computed at eachspectral data point in the frequency domain (see Methods).

While many techniques exist to facilitate in the interpretationof such data, TOPSY allows the calculated T1 or T2 relaxationtimes to be projected as a color directly onto the original1D 1H NMR spectrum of the mixture. Thus, TOPSY allowsvisual recovery of higher order information on chemicalinteractions in complex multicomponent systems, whilemaintaining relative peak intensities and multiplet structures.Although it is the protons that are characterized by therelaxation times, an “effective” T1 or T2 value can becalculated for each spectral data point, and by this means,

the differences in the relaxation times (both T1 and T2)between samples in Figure 4 are seen, highlighting theresonances that are affected by borate preservation.

By examination of the TOPSY plot based on the 1H T1

relaxation times (Figures 4A-4C), it can be seen that additionof borate simply causes a general reduction of T1 values acrossthe whole spectrum. Thus, peaks colored red without borateaddition become orange/yellow, and those originally coloredblue become cyan. This effect is probably due to an overalleffect of borate on the solution, possibly caused by a slightincrease in solution viscosity, which would cause a reductionof small molecule T1 values. This also indicates that the relativepeak intensities are also unlikely to be affected by borateaddition, and if data were to be acquired under partiallysaturating NMR conditions, borate addition would not causeany additional problems of quantitation.

Figure 2. 1H NMR spectra of a standard solution containing (A-C) citrate, (D-F) citrate/borate complex, (G-I) mannitol, and (J-L) mannitol/borate complex. A, D, G and J are data acquired at 400 MHz; B, E, H, and K are data acquired at 600 MHz; and C, F, I, and L are data acquiredat 800 MHz. Proposed structures of these compounds and their complexes are given in the left-hand panel of the figure.

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Examination of the TOPSY plots based on T2 relaxation timesshows more specific effects consistent with borate-metabolitecomplexation (see Figure 4B-F). The two main effects are ashortening of the citrate proton T2 values after addition of borateand the lengthening of the T2 values of protons, giving rise tospecific carbohydrate resonances assignable to mannitol. Thisbehavior is consistent with borate-metabolite complexation,and the direction of change of T2 will be influenced by boththe altered molecular reorientational mobility and the exchangerate. It is concluded that borate-induced changes in T2

relaxation times are small and limited to the main complexedspecies described above.

Chemometric Analysis of NMR Spectra from Borate-Treated Urine Samples. To investigate the detailed effects ofborate on the global statistical mapping of urinary metabolic NMRdata, spectral profiles of urine containing four concentrations ofborate (0, 3.07, 16.90, and 30.73 mM) at nine successive timepoints over 12 months (see Methods) were acquired at 400 MHz.The spectral data were analyzed by PCA, and the scores plot isshown in Figure 5A. Here, each data point represents one spectralprofile color-coded to indicate the concentration of borate. Dif-ferences caused by variation in concentrations of borate werelargely described by the first principal component. The corre-

sponding loadings plot (Figure 5B) denotes the 1H NMR chemicalshifts of the variables responsible for the distribution in Figure5A, and this is largely due to resonances in the chemical shiftregion δ 3.4-4.1. Close inspection of the spectra indicated thatthis sample contained mannitol, thus explaining the majority ofthe observed variation in this PCA model. The effects of storagetime at -40 °C were negligible (and not responsible for theobserved variation in PC2), consistent with our previous observa-tions.20

Finally, to investigate the extent of this within-individualvariation due to varying borate concentrations and time comparedwith interindividual variation in a metabolic analysis of epidemio-logic data set, a range of urine samples containing 10 concentra-tions of borate (0, 3.07, 6.15, 9.22, 12.29, 16.90, 21.51, 24.58, 27.66,and 30.73 mM) were added to a set of human urine samplescollected previously (n ) 200).42,43 The 600 MHz 1H NMRspectroscopic data on urine samples were collected under thesame preparation and acquisition conditions described in theMethods section. In the resulting scores plot of the first twoprincipal components based on the 1H NMR spectra (Figure 5C),the specimens with varying concentrations of borate are coloredred and the urine population metabolic data set are black. Thecauses of the natural population variance are highlighted in Figure

Figure 3. Direct infusion (negative mode) ESI spectrum of a sample containing equal molar (A) citrate:borate, (B) mannitol:borate, and (C)R-hydroxyisobutyrate:borate in water.

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5D and cover a much wider range of chemical shifts than forFigure 5B. From these results, it is clear that the variationassociated with borate concentration is negligible compared withthe interindividual biological/biochemical variation in the popula-tion samples.

DISCUSSIONWith development of innovative approaches to molecular

epidemiology, large-scale population screening of epidemiologicsamples is now feasible, providing a novel means of identifyingendogenous and exogenous biomarkers possibly associated with

increased risk of disease.42,43 It is also possible to retrospectivelyexamine samples banked years earlier, as demonstrated by ouranalysis of the INTERMAP urine samples, collected in 1966-1999and analyzed using 1H NMR spectral profiling in 2002-2004.11,25

To allow meaningful interpretation of data from banked samples,it is of key importance to isolate artifactual sources of variationthat might lead to misassignment of signals and false biomarkeridentification. Complexation with borate is one such source ofvariation in metabolic profiles, and as this is a widely used urinarypreservative, it is important to assess its influence on spectralmetabolite profiles.

Borate has been used for urine sample preservation in a largenumber of clinical and epidemiologic studies for many decades.It has been shown to prevent urine from bacterial overgrowth,44

(42) Elliott, P.; Stamler, R. Control Clin. Trials 1988, 9, 1S–117S.(43) Stamler, J.; Elliott, P.; Dennis, B.; Dyer, A. R.; Kesteloot, H.; Liu, K.; Ueshima,

H.; Zhou, B. F. J. Hum. Hypertens. 2003, 17, 591–608.

Figure 4. 600 MHz TOPSY spectra from a quality-control urine sample supplemented with different amounts of borate: (A and D) borate-freeurine sample, (B and E) the same urine sample supplemented with 3.07 mM borate, and (C and F) the same urine sample supplemented with30.7 mM borate. In A-C, the color scale represents T1 values projected onto the 1D spectrum. In D-F, the color scale represents T2 valuesprojected onto the 1D spectrum.

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enabling samples to be obtained within a variety of fields42,45 andanalyzed some time after collection. In comparison to biochem-istry, modern analytical techniques such as 1H NMR spectroscopyprovide information across the full range of metabolites inhuman urine, so it is likely that complexation with borate canaffect the NMR spectral analysis. However, previous chemo-metric investigations have shown that the presence of boratedoes not in itself impair classification of samples.25 This isconsistent with other data, which shows that borate does notinterfere with standard clinical assays, such as those fordetermining urinary creatinine or albumin.46 Nonetheless, itis essential that possible chemical alterations to a spectralprofile are understood in order to validate classification orbiomarker identification.

For this investigation, the spectral profiles of urine samplespreserved with various borate concentrations covering the range

expected in epidemiologic investigation were compared.42 A newvisualization technique (TOPSY) in which the measured T1 or T2

relaxation times of nuclei contributing to the NMR spectra arecolor-coded onto the urinary spectra enabled immediatecomparison of metabolite complex signals that are changed inrelaxation times due to borate complexation and assisted inthe identification of those metabolites that interact with borate.These interactions were confirmed by consideration of standardsolutions, using direct infusion ESI-MS, from which onepossible stoichiometry for the borate-metabolite complexeshas been proposed.

In addition to identifying metabolites that were affected byborate, from a population-screening perspective, it is importantto determine how the concentration of borate affects 1H NMRspectral profiles globally. It was shown that the overall changesin the urinary spectral profile caused by borate addition arenegligible compared with the physiological and metabolicdifferences between the individuals, despite minor spectralchanges due to interactions between borate and citrate,

(44) Meers, P. D.; Chow, C. K. J. Clin. Pathol. 1990, 43, 484–487.(45) Stamler, J. Am. J. Clin. Nutr. 1997, 65, 626S–642S.(46) Pugia, M. J.; Lott, J. A.; Clark, L. W.; Parker, D. R.; Wallace, J. F.; Willis,

T. W. Eur. J. Clin. Chem. Biochem. 1997, 35, 693–700.

Figure 5. (A) PC1 vs PC2 scores plot of 1H NMR spectral data from urine samples with varying borate concentrations and storage times. Thefour concentrations of borate are 0 mM (green), 3.07 mM (blue), 16.90 mM (red) and 30.73 mM (black) in urine at nine time points over a periodof 12 months. (B) PCA loading plot for the scores in A. (C) PC1 vs PC2 scores plot of 1H NMR spectral data from samples with varying borateconcentrations (0, 3.07, 16.90, and 30.73 mM in urine) shown in red and 200 urine sample from a typical Western population shown in black.(D) PCA loading plot for the scores in part C. All data in parts A and B were acquired at 400 MHz, and all data in parts C and D were acquiredat 600 MHz observation frequencies.

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mannitol, methylmalonate, and R-hydroxyisobutyrate. Also, theaddition of borate to urine has been shown to inhibit bacterialgrowth and therefore preserve levels of ethyl glucuronide47

(a more reliable marker of chronic alcohol consumption thanethanol), a matter of particular interest to the INTERMAP studygiven the correlation of alcohol intake with blood pressure.48

Moreover, borate has been shown to be a suitable urinarypreservative for the purpose of proteomic studies.49 We haveinvestigated these effects in urine samples from broadly healthyindividuals, but in most diseased subjects these and othermetabolites may be observed in different proportions, whichmay indicate caution if discriminating disease biomarkerscontain diols or other borate-reactive species.

We concluded that the overall changes in the urinary spectralprofile caused by borate are negligible in comparison withinterindividual biological variation and that this method of

preservation is fit for purpose in large-scale metabolic epidemiol-ogy screening study.

ACKNOWLEDGMENTL.M.S. acknowledges funding from the METAGRAD Ph.D.

program supported by AstraZeneca, Unilever, and Servier. A.D.M.acknowledges funding from the EU framework 6 MOLPAGEproject. The INTERSALT Study was supported by the Council onEpidemiology and Prevention of the International Society andFederation of Cardiology; World Health Organization; InternationalSociety of Hypertension; Wellcome Trust; National Heart, Lung,and Blood Institute of the USA; Heart Foundations of Canada,Great Britain, Japan and The Netherlands; Chicago HealthResearch Foundation; Parastatal Insurance Co. Belgium; and byother national agencies supporting local studies.

Received for review March 5, 2009. Accepted April 30,2009.

AC9004875

(47) Thierauf, A.; Serr, R.; Halter, C. C.; Al-Ahmad, A.; Rana, S.; Weinmann, W.Forensic Sci. Int. 2008, 182, 41–45.

(48) Stamler, J.; Elliott, P.; Dennis, B.; Dyer, A. R.; Kesteloot, H.; Liu, K.; Ueshima,H.; Zhou, B. F. J. Human Hypertens. 2003, 17, 591–608.

(49) Thongboonkerd, V.; Saetun, P. J. Proteome Res. 2007, 6, 4173–4181.

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