EP2435832A1

EP2435832A1 - Methods and reagents for the quantitative determination of metabolites in biological samples

Info

Publication number: EP2435832A1
Application number: EP10724355A
Authority: EP
Inventors: Cesar Marquez Gonzalez; Javier CALVO MARTÍNEZ; Niels-Christian Reichardt
Original assignee: Metabolic Renal Disease SL
Current assignee: Metabolic Renal Disease SL
Priority date: 2009-05-25
Filing date: 2010-05-25
Publication date: 2012-04-04
Also published as: WO2010136455A1

Abstract

The invention relates to a method for determining the concentration of a test metabolite in a biological sample by mass spectrometry without the need of using labelled analogues of the test metabolite. The method of the invention involves the use of a collection of reference samples containing known and increasing amounts of the test metabolite and the determination in said collection of samples the mass intensities of the test metabolite and of at least one naturally occurring isotopologue thereof. The invention also relates to computer means and kits for carrying out the invention.

Description

METHODS AND REAGENTS FOR THE QUANTITATIVE DETERMINATION OF METABOLITES IN BIOLOGICAL SAMPLES

FIELD OF THE INVENTION

The invention relates to the field of diagnostic assays and, more in particular, to the field of diagnostics based on the determination of the concentration of metabolites in a sample from a subject under study, said concentration being indicative of the presence of a given condition.

BACKGROUND OF THE INVENTION

Comprehensive analysis of small molecule metabolites in complex biological systems can provide important insight that may otherwise be difficult or impossible using targeted analysis of specific compounds. Increasingly, Liquid Chromatography coupled to Mass Spectrometry (LC/MS) is being used for metabolic analysis due in part to widespread availability and compatibility with biological samples, to the excellent sensitivity and good identification capabilities of the technique and to its compatibility with a wide-range of analytes in biological samples.

LC/MS can be used for the identification of metabolites in biological samples as well as for the quantification of known metabolites. Quantification can be relative, i.e. it only provides the ratio of the concentration of the metabolite in the test sample with respect to the concentration of the metabolite in a reference sample or absolute, i.e. it provides the concentration of metabolite in a sample.

Relative quantification is often carried out by in vivo labeling of metabolites with ²H, ¹³C, or ¹⁵N, and comparing the labeled sample with a control sample that has natural isotopic abundances. (Birkemeyer C et al, Trends Biotechnol. 2005, 23, 28- 33; Lafaye A et al., Anal. Chem. 2005, 77, 2026-2033; Wu L et al., Anal. Biochem. 2005, 336, 164-171; and, Mashego MR et al., Biotechnol. Bioeng. 2004, 85, 620-628). That strategy works fairly well for certain organisms such as yeast, bacteria, and some plants, but uniform incorporation of these isotopes into all metabolites for animals is quite difficult/expensive or impossible (e.g., metabolites from humans).

Another strategy for relative quantification is chemical labeling, which has proven to be useful for quantification in genomics (e.g., two color fluorescent dye labeling)(Lockhart DJ et al, Nature Biotechnol. 1996, 14, 1675-1680; and, Schena M et al, Science 1995, 270, 467-470) and proteomics (e.g., isotope-coded affinity tags)(Aebersold R et al., Nature 2003, 422, 198-207; Gygi SP et al., Nature Biotechnol. 1999, 17, 994-999). Relative quantification by labeling has seen limited use for metabolomics due in part to the lack of a single functional group present in all metabolites to act as the target for the labeling chemistry. Moreover, relative quantification can also be carried out using isotopic labeling. This technique is also ill-suited for metabolomic studies for the same reasons as the chemical labeling, i.e. the lack of a single functional group present in all metabolites.

WO2007109292 describes a method for relative quantification of a metabolite wherein the test and reference samples are reacted with a reagent that differs only in its isotopic kit, thereby creating heavy and light versions of derivatized metabolites, which are easily distinguished by MS. Labeled metabolites co-elute from the LC-column and appear in the mass spectrum as pairs of peaks with a mass-shift equal to the difference in mass of the two isotopic labels. The ratio of peak intensities for each pair yields the relative concentration of each metabolite between the two samples.

Tabata et al., (Anal. Chem., 2007, 79:8440-8445) have described a method for the relative quantification of an analyte by LC/MS using internal pseudostandards, i.e., metabolites which concentration does not change between the test and the reference sample.

WO0398182 describes a method for the determination of the relative amount of a protein in sample wherein both the reference samples and the test samples are metabolically labeled and combined in equal amounts. The relative amounts of the different metabolites can then be determined by analyzing the test sample, the reference sample and the mixture thereof by mass spectrometry followed by the determination of the intensity of the peaks corresponding to the atom added during metabolic labeling as well as of the isotopologues thereof.

However, relative quantification is only suitable when a reference sample is available or when detecting changes in concentration between two different time points, but does not provide absolute concentration values which are required when samples obtained from different places or time-points are to be compared.

Various strategies have been employed for quantitative LC-MS of metabolomic samples. Typically, absolute quantification of an analyte relies upon addition of an internal standard differing only in its isotopic form (the so-called isotopic dilution method). That method has been employed in many studies that target a particular compound or a small set of metabolites. (Kita Y et al, Anal. Biochem. 2005, 342, 134-

143; and, Rabaglia ME et al., Am. J. Phys. Endocrinol. Metab. 2005, 289, E218-E224). However, it is impractical to add an isotopic standard for every compound when more comprehensive metabolic profiling is required.

Consequently, some quantitative metabolic profiling has been performed without an isotopic standard. For instance, Wang WX et al., Anal. Chem. 2003, 75, 4818-4826 have described a method for the absolute quantification of proteins and metabolites in a sample which is based on the presence in the sample of molecules (metabolites or proteins) which show constant concentration among the different samples. This allows the use of the average intensity of the peaks corresponding to the molecules of constant concentration to normalize the intensity of the peaks corresponding to the target metabolite.

Quantification in this manner is less precise, but adequate reproducibility has been obtained in many cases despite the well-known problem of ion- suppression during electrospray ionization. (Choi BK et al., Chromatogr. A 2001, 907, 337- 342; Constantopoulos TL et al., Am. Soc. Mass Spectrom. 1999, 10, 625-634; Sterner JL et al., Mass Spectrom. 2000, 35, 385-391; and, Tang L et al., Anal. Chem. 1993, 65, 3654- 3668). Currently, the application of LC-MS for quantitative determination of an analyte in a sample involves the introduction of a known amount of a chemically analogous extraneous substance as an internal standard (i.e., "spiking" of a standard reference material), being said analogue chemically identical and isotopically labeled or based on chemical similarity.

Mass spectrometry (MS) is rapidly becoming a method of choice for analysis of proteins, peptides and other biological molecules. Laser desorption/ionization mass spectrometry methods such as matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and surface enhanced laser desorption/ionization mass spectrometry (SELDIMS) procedures are very sensitive analytical methods and are probably the MS procedures most compatible with biological samples. Further, the ability of these procedures to generate high-mass ions at high efficiency from sub- picomole quantities of biological macromolecules makes these techniques extremely useful for macromolecule analysis and macromolecule identification in biological samples. Analysis of peptide analytes in crude biological samples, such as blood, plasma, or serum, however offers special problems for mass spectrometry analysis.

Laser desorption/ionization methods of mass spectrometry ("LDI-MS") for protein analytes in complex sample mixtures, such as serum or urine, pose particular problems for quantization. In particular, peak intensity of an analyte can vary based on the nature of the protein milieu in which it is found, variances in sample handling and variances in instrument performance. One way to overcome these problems is to introduce normalization standards into a sample against which the analyte can be compared. Another method is to construct a standard curve of the analyte on which the quantity of the analyte can be measured. However, standard curves can suffer if the calibration series is not matched with the sample being tested.

The use of LDI-MS to quantify an analyte within a biological sample may involve certain difficulties. The laser desorption process is a complex and poorly understood event that depends on the interaction of a laser ionization source and co-crystals consisting of both protein sample and desorption matrix. In the laser desorption event, ionization of any one analyte cannot occur independent of any other analyte exposed at the same time to the ionization source. When two samples containing an analyte as well as a number of other proteins, where the other proteins are vastly different in either concentration or composition, are ionized the relative abundance of ions formed for the analyte in each of the samples may not be correlated with their concentration. Thus, the ability to quantify the analyte becomes problematic.

Even when no common standard analytical technique has emerged yet for quantitative metabolomics, atmospheric pressure ionization (API) techniques such as atmospheric pressure chemical ionization (APCI) or electrospray ionization (ESI) have become well accepted in the analysis of complex mixtures like bio fluids, in special when coupled to a previous fractioning process such as HPLC. API sources permit the direct transportation of ionized analytes from liquid into gas-phase. The coupling of chromatographic techniques helps to circumvent matrix effects like ion suppression due to competition in the ionization process between different analytes or due to the presence of surfactants and inorganic salts.

The methods of this invention provide a method of standardizing an assay using a calibration curve with absolute standards achieved by minimizing interference from non-analyte (i.e., background) proteins naturally associated with the biological sample while simultaneously providing a complex set of invariant internal standards. This results in a normalized analyte value that can be quantified directly from clinical or test samples by comparison to the calibration curve.

SUMMARY OF THE INVENTION

In a first aspect, the invention relates to a method for determining the concentration of a metabolite (M) of known m/z in a test sample by mass spectrometry which comprises the steps of:

(i) performing mass spectrometry on the test sample and in at least two reference samples of the same nature as the test sample to which known and different amounts of M have been previously added, (ii) determining the peak intensity of M in the spectra obtained from the test sample and of M and of at least one naturally-occurring isotopologue of M in the spectra obtained from the reference samples and

(iii) determining the concentration of M in the test sample by interpolating the peak intensity of M in the test sample within a calibration curve obtained from (a) the intensities of the peaks of M and of the at least one naturally-occurring isotopologue of M in the reference samples and (b) the concentrations of M and of the at least one naturally- occurring isotopologue of M in said reference samples.

In a second aspect, the invention relates to a method for the determination of the concentration of a metabolite (M) in a test sample by mass spectrometry comprising the steps of

(i) performing mass spectrometry on the test sample and in at least one reference sample of the same nature than the test sample wherein said at least one reference sample contains a known concentration of M,

(ii) determining the peak intensity of M in the test sample and of M in the at least one reference sample and

(iii) determining the concentration of M in the test sample by applying a proportionality factor to the concentration of M in the reference sample, wherein said proportionality factor is the ratio of the peak intensities of M in the test sample and in the reference sample.

In another aspect, the invention relates to a computer program or a computer-readable media containing means for carrying out a method as defined in the first and second aspects of the invention.

In another aspect, the invention relates to a kit for the determination of the concentration of an analyte in a test sample comprising

(i) a reference sample of the same nature as the test sample and (ii) information as to the concentration of the analyte in the test sample, its retention time and as to the proportionality factor between the analyte and the peak intensity in the mass spectra. BRIEF DESCRIPTION OF THE FIGURES

Figure 1. The selected ion monitoring (SIM) chromatogram shows the increase of intensity observed for m/z = 120.066 ± 0.02Da and corresponding to the protonated lighter isotopologue (M) of threonine as its concentration increases in the sample solution. The processed chromatograms here presented have been smoothed twice by a mean method. They also have been aligned using an offset time within ±4sec.

Figure 2. The selected ion monitoring (SIM) chromatogram shows the increase of intensity observed for m/z = 121.069 ± 0.02Da and corresponding to the protonated heavier isotopologue (M+ 1) of threonine as its concentration increases in the sample solution. The processed chromatograms here presented have been smoothed twice by a mean method. They also have been aligned using an offset time within ±4sec.

Figure 3. The selected spectra shows the normalized isotopic distribution found for protonated threonine in the test sample. Notice that the signal corresponding to m/z = 121.021 does not correspond to the mentioned threonine, and its intensity is not considered in the SIM chromatograms shown in Figures 4 and 5.

Figure 4. The selected ion monitoring (SIM) chromatogram shows the intensity's increments observed for m/z = 205.098 ± 0.02Da and corresponding to the protonated lighter isotopologue (M) of tryptophan as its concentration increases in the sample's solution. The processed chromatograms here presented have been smoothed twice by a mean method. They also have been aligned using an offset time within ±4sec.

Figure 5. The selected ion monitoring (SIM) chromatogram shows the increase of intensity observed for m/z = 206.101 ± 0.02Da and corresponding to the protonated heavier isotopologue (M+ 1) of tryptophan as its concentration increases in the sample solution. The processed chromatograms here presented have been smoothed twice by a mean method. They also have been aligned using an offset time within ±4sec.

Figure 6. The selected spectra shows the normalized isotopic distribution found for protonated tryptophan in the test sample. Notice that the signals corresponding to m/z = 205.020 and 205.941 do not correspond to the mentioned tryptophan, and their intensities are not considered in the SIM chromatograms shown in Figures 1 and 2.

DETAILED DESCRIPTION

The authors of the present invention have found that the quantitative determination of an analyte in a sample can be improved by using a standard curve prepared from the same sample to which increasing and known concentrations of the analyte has been added. Since the standard curve samples and the test samples have a very similar composition, undesired artifacts due to differences between the standard curve samples and the test samples, such as ion suppression, are avoided.

Thus, in a first aspect, the invention relates to a method (hereinafter, first method of the invention) for determining the concentration of a metabolite (M) of known m/z in a test sample by mass spectrometry which comprises the steps of:

(i) performing mass spectrometry on the test sample and in at least two reference samples of the same nature as the test sample to which known and different amounts of M have been previously added,

(ii) determining the peak intensity in the spectra obtained from the test sample of M and of M and at least one naturally-occurring isotopologue of M in the spectra obtained from the reference samples and

As used herein, "metabolite" refers to any analyte of interest that may be determined. Non- limiting examples of analytes can include, but are not limited to, proteins, peptides, nucleotides, oligonucleotides (both DNA or RNA), carbohydrates, lipids, steroids, amino acids and/or other small molecules with a molecular weight of less than 1500 Daltons. The metabolite or metabolites can be natural or synthetic, endogenous or exogenous.

The term "m/z" is used herein interchangeably with mass/charge, mass/ionization ratio or mass-to-charge ratio) and refers to the ratio between the mass of an object and the charge of the same object. The mass is customarily expressed in terms of atomic mass units (amu), also called Daltons (Da). The charge is customarily expressed in terms of multiples of elementary charge, which is the amount of charge in an electron or a proton. Because the ion usually has a single charge, the m/z ratio value is usually coincident with the mass of the ion expressed in Daltons, or its molecular weight (MW).

The mass-to-charge ratio of a target metabolite can be determined using any conventional mass spectrometry technique. A time-of- flight mass analyzer is a preferred mass analyzer for measuring the desorbed and ionized target, and even more preferably, the time-of- flight mass analyzer can be preceded by an ion reflector to correct for kinetic energy differences among ions of the same mass. Another preferred enhancement of the time of flight mass analyzer is a short, controlled, delay between the desorption and ionization of the target and the application of the initial acceleration voltage by the mass analyzer. Other mass analyzers, including magnetic ion cyclotron resonance instruments, deflection instruments, quadrupole mass analyzers, and other instruments known to one skilled in the art are also suitable within the scope of the invention for determination of the m/z of the test analyte. In a preferred embodiment, the m/z of a test analyte is determined by preparing different samples having the same composition and which contain increasing amounts of the test analyte. These samples are then analyzed by mass spectrometry. Ideally, the mass spectra of the different samples are identical except for the region wherein the test analyte is found, which should show increasing intensities. The m/z of the peak which intensity increases as the concentration of analyte in the sample increases is then considered to be the m/z of interest for the test analyte.

The term "sample", as used herein, is understood as any complex composition wherein the concentration of at least one of the components is unknown. The method according to the invention can be applied to any type of samples, including chemical analysis samples, food samples, environmental samples and biological samples. In a preferred embodiment, the determination is carried out in a biological sample. The expression "biological sample", as used herein, relates to any sample having a biological origin. Preferably, the biological sample is a fluid or an extract. By "biological sample" is meant any solid or fluid sample obtained from, excreted by, or secreted by any living organism, including single-celled micro-organisms (such as bacteria and yeasts) and multicellular organisms (such as plants and animals, for instance a vertebrate or a mammal, and in particular a healthy or apparently healthy human subject or a human patient affected by a condition or disease to be diagnosed or investigated). A biological sample may be a biological fluid obtained from any location (such as blood, plasma, serum, urine, bile, cerebrospinal fluid, aqueous or vitreous humor, or any bodily secretion), an exudate (such as fluid obtained from an abscess or any other site of infection or inflammation), or fluid obtained from a joint (such as a normal joint or a joint affected by disease such as rheumatoid arthritis). Alternatively, a biological sample can be obtained from any organ or tissue (including a biopsy or autopsy specimen) or may comprise cells (whether primary cells or cultured cells) or medium conditioned by any cell, tissue or organ. If desired, the biological sample is subjected to preliminary processing, including preliminary separation techniques. For example, cells or tissues can be extracted and subjected to subcellular fractionation for separate analysis of biomolecules in distinct subcellular fractions, e. g., proteins or drugs found in different parts of the cell. A sample may be analyzed as subsets of the sample, e. g., bands from a gel. In a preferred embodiment, the biological sample is blood serum or plasma.

In step (i) of the first method of the invention, the test sample is analyzed by mass spectrometry using standard mass spectrometry equipment. In parallel, mass spectrometry is applied to a number of reference samples of the same nature as the test sample to which known and different amounts of M have been previously added.

It will be understood that the biological sample can be analyzed as such or, alternatively, the metabolites may be first extracted from the sample prior to analysis and then the metabolite extract is then analyzed. If the metabolites are extracted prior to analysis, different extraction methods are available to the skilled person. The selection of one or other extraction method will depend on the class of metabolites/small molecules that are targeted from a particular analysis. Suitable extraction methods include "Extraction of free metabolite pools", "Vapor Phase Extraction", and "Total Metabolite Extraction". The first type of extraction, "Extraction of free metabolite pools", is mainly used in metabolomics research. In this case free intracellular metabolite pools are obtained from a biological sample through methanol-water extraction for polar metabolites, or chloroform extraction for non-polar metabolites. The second type of extraction, "Vapor Phase Extraction", refers to the extraction of metabolites that are volatile at room temperature. The metabolites are expelled from the biological sample in the vapor phase. These metabolites are either measured directly by connecting the flask or reactor in which the vapors are generated to the analytical instrument or by absorbing first the vapors in charcoal/solvent and then analyzing the acquired solution. The third type of extraction, "Total Metabolite Extraction", refers to the extraction of the free metabolite pools along with the metabolites that have been incorporated in cellular macromolecules, e.g. lipids, proteins etc. The present invention provides extraction of a particular class of metabolites from macromolecules (e.g. amino acids from proteins or sugars from cell wall components). The present invention also provides a combined high-throughput method which extracts all metabolites simultaneously.

Alternatively, the metabolite quantification can be carried out in the biological sample. In this case, the sample may be prepared to enhance detectability of the markers. For example, to increase the detectability of markers, a blood serum sample from the subject can be preferably fractionated by, e.g., Cibacron blue agarose chromatography and single stranded DNA affinity chromatography, anion exchange chromatography, affinity chromatography (e.g., with antibodies) and the like. The method of fractionation depends on the type of detection method used. Any method that enriches for the metabolite of interest can be used. Typically, preparation involves fractionation of the sample and collection of fractions determined to contain the biomarkers. Methods of pre-fractionation include, for example, size exclusion chromatography, ion exchange chromatography, heparin chromatography, affinity chromatography, sequential extraction, gel electrophoresis and liquid chromatography. The analytes also may be modified prior to detection. These methods are useful to simplify the sample for further analysis. For example, it can be useful to remove high abundance proteins, such as albumin, from blood before analysis.

In yet another embodiment, a sample can be pre- fractionated by removing proteins that are present in a high quantity or that may interfere with the detection of markers in a sample. Proteins in general may be removed by using conventional techniques such as precipitation using organic solvents such as methanol precipitation, ethanol, acetonitrile, acetone or combinations thereof, in particular, combination of methanol, acetone and acetonitrile, acid precipitation using, for example, trichloroacetic acid or perchloric acid, heat denaturation and any combination of organic solvent, acid and heat precipitation. In the case of a blood or serum sample, serum albumin or other proteins abundant in serum such as apo lipoproteins, glycoproteins, inmunoglobulins may obscure the analysis of markers since they are present in a high quantity. Thus, it may be sufficient to remove one or more of the above proteins albumin in order to detect the metabolites or minor proteins. For this purpose, the blood serum sample can be pre-fractionated by removing serum albumin. Serum albumin can be removed using a substrate that comprises adsorbents that specifically bind serum albumin. For example, a column which comprises, e.g., Cibacron blue agarose (which has a high affinity for serum albumin) or anti-serum albumin antibodies can be used. In yet another embodiment, a sample can be pre-fractionated by isolating proteins that have a specific characteristic, e.g. are glycosylated. For example, a blood serum sample can be fractionated by passing the sample over a lectin chromatography column (which has a high affinity for sugars). Many types of affinity adsorbents exist which are suitable for pre-fractionating blood serum samples. An example of one other type of affinity chromatography available to pre- fractionate a sample is a single stranded DNA spin column. These columns bind proteins which are basic or positively charged. Bound proteins are then eluted from the column using eluants containing denaturants or high pH. Thus there are many ways to reduce the complexity of a sample based on the binding properties of the proteins in the sample, or the characteristics of the proteins in the sample.

In yet another embodiment, a sample can be fractionated using a sequential extraction protocol. In sequential extraction, a sample is exposed to a series of adsorbents to extract different types of biomolecules from a sample. As used herein, "mass spectrometry" (MS analysis) means an analytical technique to identify unknown compounds including: (1) ionizing the compounds and potentially fractionating the compounds parent ion formed into daughter ions; and (2) detecting the charged compounds and calculating a mass-to-charge ratio (m/z). The compounds may be ionized and detected by any suitable means. A "mass spectrometer" includes means for ionizing compounds and detecting charged compounds.

The ionization source for the mass spectrometric analysis includes, but is not limited to, electron impact (EI), chemical ionization (CI), atmospheric pressure chemical ionization (APCI), electrospray ionization (ESI), sonic spray ionization, matrix-assisted laser- desorption ionization (MALDI), or the like. In a preferred embodiment, ionization is carried out by electrospray ionization (ESI).

Mass analyzers suitable for separating and detecting the heavy- and light-labeled forms of the analyte end-products are suitable for use with the instant labeling reagents, such as, but not limited to, magnetic sector, double focusing, time-of- flight (TOF), linear ion trap, quadrupole (Q), triple quadrupole (QQQ), quadrupole time-of- flight (QTOF), ion- trap time-of- flight, Fourier transform spectrometers such as the ion cyclotron resonance (FT-ICR) and Orbitrap, and the like.

The above mentioned ionization methods generally produce what is known in the art as a protonated molecule, meaning the addition of a proton or a hydrogen nucleus, [M+H]⁺ where M signifies the molecule of interest, and H signifies the hydrogen ion, which is the same as a proton. Some ionization methods will also produce analogous ions. Analogous ions may arise by the addition of an alkaline metal cation, rather than the proton discussed above. A typical species might be [M+Na]⁺ or [M+K]⁺. The analysis of the ionized molecules is similar irrespective of whether one is concerned with a protonated ion as discussed above or dealing with an added alkaline metal cation. The major difference is that the addition of a proton adds one mass unit (typically called one Dalton), in case of the hydrogen ion (i.e., proton), 23 Daltons in case of sodium, or 39 Daltons in case of potassium. These additional weights or masses are simply added to the molecular weight of the molecule of interest and the MS peak occurs at the point for the molecular weight of the molecule of interest plus the weight of the ion that has been added. These ionization methods can also produce negative ions. The most common molecular signal is the deprotonated molecule [M-H]^", in this case the mass is one Dalton lower than the molecular weight of the molecule of interest. In addition, for some compounds it will be produced multiply charged ions. These are of the general identification type of [M+nH]ⁿ⁺, where small n identifies the number of additional protons that have been added.

The reference samples are prepared by adding known and increasing amounts of the analyte which concentration is to be determined. The skilled person will appreciate that the number of samples in the collection of reference samples is not limiting as long the reference values are sufficient to obtain statistically significant values. The number of samples in the collection may be as low as two, preferably three, more preferably four, five, six, seven, eight, nine, ten or more.

The term "same nature", as used herein, implies that the reference samples are of the same origin as the test sample. By way of an example, if the test sample is plasma, the reference samples are obtained by adding increasing amounts of the test analyte to either two or more aliquots of the same plasma that is to be determined or, alternatively, to plasma preparations which are obtained by pooling a plurality of plasma samples. The number of samples that can be pooled in order to obtain a test sample will vary but it may contain at least 1, at least 10, at least 100, at least 200, at least 300, at least 400, at least 500 or more samples.

The reference samples have been supplemented with known and different concentrations of M so that each reference sample will contain a concentration of final M which will be the result of the addition of the unknown concentration of M in the sample plus the concentration of the added M. Preferably, the amounts of M added to the reference samples will be such that the final concentration in the reference sample will be as low as 5% above the estimated concentration for the endogenous M and as much as 10 times the estimated concentration for the endogenous M. For example, to determine a endogenous test analyte concentration in the rank of 5 μM, the reference samples of the collection are prepared so that they contain, 5.0, 5.1, 5.2, 5.3, 5.4, 5.5, 6.0, 6.5, 7.0, 7.5, 8.0, 9.0, 9.5, 10, 35, 40, 45 and/or 50 μM of M.

Step (ii) of the first method of the invention involves the determination of the peak intensity of M in the spectra obtained from the test sample and of the peak intensities of M and of at least one naturally-occurring isotopologue of M in the reference samples.

The term "peak intensities", as used herein, relates to the number of incident ions able to trigger a pulse in a mass spectrometer detector during a limited time. Counts-per- second (cps) is the commonly used unit for peak intensity.

As used herein, the term "naturally occurring isotopologue" refers to a species that differs from a specific compound only in the isotopic composition thereof. Thus, it will be clear to those of skill in the art that the number and concentration of isotopologues of a given compound in a given sample will depend on the natural abundance of the isotopes as well as on the number of atoms in the compound that may be substituted by an isotope. Thus, in the case of the isotopologues resulting from the replacement of a carbon atom ¹²C by its ¹³C isotope, compounds having a single carbon atom will typically contain 1.1122% of the ¹³C isotope, since this is the natural abundance of ¹³C in nature. In the case of compounds having a single nitrogen atom, the isotopologue resulting from the replacement of the single nitrogen atom ¹⁴N by the ¹⁵N isotope will typically appear in nature with an abundance of 0.3673% since this is the natural abundance Of ¹⁵N.

Isotopologues are usually classified as "lighter" and "heavier" isotopologues. The terms "lighter isotopologue" and "lighter atom isotopologue" as used herein, refer to a species that differs from a compound of this invention in that it comprises one or more light isotopic atoms. For instance, lighter isotopologues would be molecules wherein positions containing deuterium ²H or ¹³C are occupied by ¹H or ¹²C. The terms "heavier isotopologue" and "heavier atom isotopologue" as used herein, refer to a species that differs from a compound of this invention in that it comprises one or more heavy isotopic atoms. For instance, heavier isotopologues would be molecules wherein positions containing ¹²C or ¹⁴N are occupied by ¹³C or ¹⁵N. Suitable isotopologues that can be measured in the method of the present invention are those containing one or more ¹⁵N, ¹⁴C, ¹³C, ¹³N, ¹⁸O and ³⁴S. In a preferred embodiment, the isotopologue used in the method of the invention is a heavier isotopologue.

If the compound contains more than one atom which may be substituted by an isotope thereof, several isotopologues may exist of the same compound. These isotopologues are usually referred to M+l, M+2, etc. The M+l isotopologue is usually a family of isotopic isomers (isotopomers) wherein one of the positions comprises the isotope, having the M+l isotopologue family as many isotopomers as numbers of atoms in the molecule that may be substituted by the isotopic form. This situation may result in isotopologues pattern having two or more peaks. As mentioned above, the relative abundance of ¹²C versus ¹³C on the earth is ¹²C at 98.9% and ¹³C at 1.1% respectively, in any naturally occurring sample of carbon. Each of these different carbon isotopes have identical chemical values and have weights that differ by one Dalton. For a molecule containing only carbon atoms the probability of there being one ¹³C at any one site is 1.1%, the probability of any other site being ¹²C or ¹³C is unaffected by the selection at any other site. Therefore the probability of there being one single ¹³C among 100 carbon atoms is given by 100x0.011(1-0.011)^{(100 1)} = 0.37, meaning that there will be several peaks, the lighter peak having all 100 ¹²C atoms with a probability of (1- 0. Oi l)¹⁰⁰ = 0.33, and a second peak that is 11% taller than the first peak and located one m/z unit higher. Thus, a compound having a hundred carbon atoms would be likely -a probability of 0.67- to have one or more of the one hundred ¹²C atoms replaced by a ¹³C atom. As a result of the substitution of several of the one hundred ¹²C atoms by a ¹³C atom, the MS spectrum of the molecule is likely to have several peaks separated from each other by one mass unit. The roughly equal height of the two first isotopologues peaks indicates that about half of the individual molecules of these two have had a random one of the ¹²C atoms replaced by a ¹³C atom. One peak represents the molecule containing all ¹²C atoms, and the second peak at one Dalton higher representing the same chemical molecule, containing all ¹²C atoms but one ¹³C atom. Further, there will be yet another peak having about 61% of the height of the first peak, in which there will be two random ¹²C atoms replaced by ¹³C atoms, thus resulting in a mass two Daltons higher than the base isotope molecule. There are further isotopologues mass spectra peaks representing three ¹³C substitutions and having about 22% of the height of the first ¹²C peak, and so on. Thus, any compound containing carbon will always produce multiple mass spectra peaks, large organic molecules containing in 80 to 100 carbons will appear as several peaks separated by one m/z unit.

As used herein, "natural isotopic abundance" refers to the level (or distribution) of one or more isotopologues found in a compound based upon the natural prevalence of an isotope or isotopes in nature. For example, a natural compound obtained from living plant matter can typically contain about 1.08 % ¹³C relative to ¹²C.

Step (iii) of the first method of the invention involves the determination of the concentration of M in the test sample by interpolating the peak intensity of M in the test sample within a calibration curve obtained from (a) the intensities of the peaks of M and of the at least one naturally-occurring isotopologue of M in the samples of the collection of reference samples and (b) the concentrations of M and of the at least one naturally- occurring isotopologue of M in said reference samples.

As used herein, "interpolation" means the process of calculating a new point between two existing data points. The interpolation process comprises comparing the peak intensity within the test sample with a data set which contains at least two pairs of peak intensity/concentration values obtained from the reference samples. The skilled person will appreciate that many methods exist for the interpolation of a given peak intensity value within a correspondence table reflecting peak intensities as a function of metabolite concentration. By way of example, the interpolation can be carried out using methods such as piecewise constant interpolation (also known as nearest neighbour interpolation), linear interpolation, polynomial interpolation, spline interpolation, rational interpolation, trigonometric interpolation, bilinear interpolation, bicubic interpolation and the like. As it will be appreciated, the accuracy of the interpolation method will depend on the number of values included in the standard data set, although it is possible to carry out an interpolation with only a single pair of values. Preferably, the interpolation is carried out using a data set comprising at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, at least eleven pairs of values. The results of the interpolation applied to the peak intensities of the test sample will provide the concentration of the metabolite in said test sample. In a preferred embodiment, the interpolation step is carried out using a calibration curve which contains the concentrations of M and those of at least one isotopologue in each of the reference samples in the X axis and the peak intensities associated with M and with the isotopologues for each of the reference samples in the Y axis. It will appreciated that, given that the concentrations of M added to each of the reference samples are known and given that the natural abundance of naturally occurring isotopes for a given element is known, the concentrations of the naturally occurring isotopologue which are added to each of the reference samples can be immediately calculated. By way of example, if the naturally occurring isotopologue is a molecule carrying a ¹³C atom and containing a single carbon atom, and given that the natural abundance of ¹³C is 1.08 % , the concentration of the first heavier isotopologue will be 1.08% of the concentration of the test analyte.

In this way, the calibration curve includes peak intensity values for each of the concentrations of M and for each of the concentrations of the at least one naturally occurring isotopologue.

In a preferred embodiment, the interpolation is carried out by linear regression analysis, In this case, a proportionality constant (m) or slope is calculated as a function of the concentration of metabolite added to the sample. Ideally, being I₀ the intensity signal in the test sample, C₀ the metabolite concentration also in the test sample, I₁ the intensity signal in the reference sample i and X₁ the known concentration of metabolite added in reference sample i, the following equations apply:

l_o 771L_O + 'noise

I₁ = m(C_o + X₁) + I_noise

I₁ - I₀ = m(C_o + X₁) + I_noise - (mC_o + I_noise)

AI₁=InX₁ ; m = ψ Thus, the proportionality constant m is, as expected, dependent on the X₁, but not of C₀ or the noise level (I_nOise).

The use of an isotopologue M* in the fitting allows interpolating the value of C₀, avoiding the difficulties of an extrapolation. The values obtained from M* can join the values from the M in the calculation of m considering

AI₁- = I₁- - I^* X₁- = (M^* Percentage) x X₁

The lower limit for the reliability in the calculation of a metabolite concentration in the test sample is independent of the concentrations values used for the determination of C₀. In principle, there is no lower limit since the entire MS methodology is based on the linear relation C α /(I). However, and based only on the interpolation, the lower limit could be defined as the concentration of the naturally occurring lighter isotopologue in the test sample.

In step (iii) of the method of the invention, the concentration of C₀ in the test sample is calculated from the proportionality constant/slope m using the formula

„ O 'noise

^L° ^~ m

In a preferred embodiment, the analysis may also be performed subsequent to a separation of the test sample. A wide variety of techniques for separating the metabolites within the test sample are well known to those skilled in the art (see, for example, Laemmli, Nature 1970,227 : 680-685 ; Washburn et al. , Nat. Biotechnol. 2001, 19: 242-7; Schagger et al. , Anal. Biochem. 1991, 199:223-31) and may be employed according to the present invention. By way of example, the test sample may be fractionated on the basis of charge (e. g. , by chromatofocusing or isoelectric focusing), of electrophoretic mobility (e.g. by non-denaturing electrophoresis or by electrophoresis in the presence of a denaturing agent such as urea or sodium dodecyl sulfate (SDS), with or without prior exposure to a reducing agent such as 2- mercaptoethanol or dithiothreitol), by chromatography, including LC, FPLC, and HPLC, on any suitable matrix (e. g., gel filtration chromatography, ion exchange chromatography, reverse phase chromatography). In a preferred embodiment, the separation is carried out using chromatography.

Chromatography, in general, is a method for mixture component separation that relies on differences in the flowing behavior of the various components of a mixture/solution carried by a mobile phase through a support/column coated with a certain stationary phase. Specifically, some components bind strongly to the stationary phase and spend longer time in the support, while other components stay predominantly in the mobile phase and pass faster through the support. The criterion based on which the various compounds are separated through the column is defined by the particular problem being investigated and imposed by the structure, composition and binding capacity of the stationary phase. For example, a stationary phase could be constructed such that the linear and low molecular weight molecules elute faster than the aromatic and high- molecular weight ones. As the components elute from the support, they can be immediately analyzed by a detector or collected for further analysis. A vast number of separation methods, and in particular chromatography methods, are currently available, including Gas Chromatography ("GC"), Liquid Chromatography ("LC"), Ion Chromatography ("IC"), Size-Exclusion Chromatography ("SEC"), Supercritical-Fluid Chromatography ("SFC"), Thin-Layer Chromatography ("TLC"), and Capillary Electrophoresis ("CE"). Gas Chromatography, can be used to separate volatile compounds. Liquid chromatography ("LC") is an alternative chromatographic technique useful for separating ions or molecules that are dissolved in a solvent. The principle of GC and LC separation is the same, their main difference lies on the phase in which the separation occurs (vapor vs. liquid phase). In addition, GC is used primarily to separate molecules up to 650 atomic units heavy, while, in principle, a LC can separate any molecular weight compounds. Suitable types of liquid chromatography that can be applied in the method of the invention include, without limitation, reverse phase chromatography, normal phase chromatography, affinity chromatography, ion exchange chromatography, hydrophilic interaction liquid chromatography (HILIC), size exclusion chromatography and chiral chromatography. In a preferred embodiment, the chromatographic separation is carried out by HPLC. High-pressure liquid chromatography (HPLC) is a separative and quantitative analytical tool that is generally robust, reliable and flexible. Suitable HPLC techniques for fractionation of analytes include reverse-phase HPLC and normal phase HPLC.

Reverse-phase (RP) chromatography involves a nonpolar stationary phase and a polar mobile phase. Typically, the stationary phase that is characterized by alkyl chains of specific length immobilized to a silica bead support. Typical stationary phase for reversed phase HPLC include alkyl hydrocarbons such as octadecyl (C 18) is the most common stationary phase, but octyl (C8) and butyl (C4) are also used in some applications. In reversed phase chromatography, the most polar compounds elute first with the most nonpolar compounds eluting last. The mobile phase is generally a binary mixture of water and a miscible polar organic solvent like methanol, acetonitrile or THF. Retention increases as the amount of the polar solvent (water) in the mobile phase increases. The designations for the reversed phase materials refer to the length of the hydrocarbon chain. RP-HPLC is suitable for the separation and analysis of various types of compounds including without limitation biomolecules, (e.g., glycoconjugates, proteins, peptides, and nucleic acids, and, with mobile phase supplements, oligonucleotides).

Aqueous normal phase chromatography (ANP) is a chromatographic technique wherein the stationary phase is polar and the mobile phase is nonpolar. Typical stationary phases for normal phase chromatography are silica or organic moieties with cyano and amino functional groups. In normal phase chromatography, the most nonpolar compounds elute first and the most polar compounds elute last. The mobile phase consists of a very nonpolar solvent like hexane or heptane mixed with a slightly more polar solvent like isopropanol, ethyl acetate or chloroform. Retention increases as the amount of nonpolar solvent in the mobile phase increases.

In order to fractionate the test and reference samples prior to their analysis by mass spectrometry, the samples containing the metabolites are injected into a HPLC column, typically silica based C 18. In general, an aqueous medium is used to elute the inorganic salts, while the metabolites are eluted with a mixture of aqueous solvent (water) and organic solvent (acetonitrile, methanol, propanol). The aqueous phase is generally HPLC grade water with 0.1% acid and the organic solvent phase is generally an HPLC grade acetonitrile or methanol with 0.1% acid. The acid is used to improve the chromatographic peak shape and to provide a source of protons in reverse phase LC/MS. The acids most commonly used are formic acid, trifluoro acetic acid, and acetic acid. In RP HPLC, compounds are separated based on their hydrophobic character. With an LC system coupled to the mass analyzer through an ESI source and the ability to perform data-dependant scanning, it is now possible in at least some instances to distinguish metabolites in complex mixtures containing more than 50 components without first purifying each metabolite to homogeneity. Where the complexity of the mixture is extreme, it is possible to couple ion exchange chromatography and RP-HPLC in tandem to identify proteins from mixtures containing in excess of 1,000 proteins.

While the instant invention is exemplified using an ESI-TOF mass spectrometer and reverse-phase UPLC, it is not limited to this arrangement. Other known mass spectrometry and separation methods may be used as well.

When the test and the reference samples are fractionated prior to mass spectrometry analysis, a mass spectrum will be obtained for each of the fractions obtained during the chromatography. Typically, the test compound elutes in two or more chromatographic fractions, known as retention time interval, so that the total intensity of the compound can be determined by integrating the peak intensity within retention time interval. Thus, in a preferred embodiment, the peak intensities of M and/or of the at least one naturally- occurring isotopologue of M in each sample are determined in step (ii) by integration of the peak intensities within a retention time interval, wherein said interval is determined using a known analyte of known m/z present in a continuous mode within the retention time interval of M.

It will be appreciated that the integration of the peak areas over a retention time interval can only be carried out once the retention time interval in which the test compound elutes is known. Thus, in a preferred embodiment, the retention time interval of the test compound will be that where the monitored intensity of the selected ion increases with the concentration of metabolite in the reference samples. In a preferred embodiment, the time interval in which the integration is to be carried out is determined using the retention time of M and the naturally occurring isotopologue of M in the most concentrated of the reference samples. The most concentrated reference sample provides a clear intensity increment of the corresponding m/z exact value when compared to the test sample.

In a preferred embodiment, the integrated signal intensity of M or of M and the naturally occurring isotopologue of M are normalized by dividing them by the integrated signal intensity of a known analyte within the retention time interval of M. The analyte is permanently injected during the entire experiment via a HPLC cross settled post-column and prior the ionization source. Two reasons justify the continuous injection of an exogenous analyte during the time expand of the quantification experiment. First, it is used as internal standard for the unambiguous determination of exact mass of the different metabolites. At the same time, the analyte peak intensity is used for the normalization of the peak intensity of the metabolite between the collected spectra. This way, the normalization precludes the effects of unexpected system instability.

The first method of the invention allows the quantification of a test analyte in a test sample. This determination is useful for diagnostic/prognostic purposes if it is known that the concentration of the analyte correlates with a given disease or condition.

Moreover, it also allows obtaining a quantified sample which can be used as a reference for the determination of the concentration of the same analyte in other samples of the same nature. This makes possible the determination of the concentration of an analyte by comparing with the intensity value obtained in a single reference sample without the need of preparing a calibration curve. The skilled person will appreciate that this method has certain advantages since the method can be carried out without the need of using a collection of samples having increasing concentrations of the test analyte or adding internal isotopologue standards.

Thus, in another aspect, the invention relates to a method (hereinafter, the second method of the invention) for the determination of the concentration of a metabolite (M) in a test sample by mass spectrometry comprising the steps of (i) performing mass spectrometry on the test sample and on at least one reference sample of the same nature than the test sample wherein said at least one reference sample contains a known concentration of M, (ii) determining the peak intensity of M in the test sample and of M in the at least one reference sample and

The term "test sample" is as defined previously in the context of the first method of the invention. The term "reference sample" as understood in the context of the second method of the invention, relates to a sample wherein the concentration of the test analyte is known. This concentration of the analyte in the reference sample can be determined using any method known in the art but preferably, the concentration is determined using the first method of the invention.

Other terms used to define the second method of the invention have been explained in detail in the context of the first method of the invention.

Step (i) involves performing mass spectra on the test sample and on the reference sample. As it occurs with the first method of the invention, the sample can be of any origin, more preferably a biological sample and, even more preferably, a biofluid and, even more preferably, urine or plasma. Moreover, the sample may be applied as such or may be fractionated prior to the mass spectrometry so as to separate the test analyte from other compounds present in the sample. In a preferred embodiment, separation is carried out by reverse phase liquid chromatography.

Step (ii) of the second method of the invention involves the determination of the total peak intensities of the test analyte in the test samples and in the reference sample from the mass spectra obtained from both samples. As explained above, this determination can be carried out on the peak corresponding to M or, if the sample has been fractionated prior to the mass spectrometric analysis, on an interval of retention times wherein substantially all the test compound elutes.

Step (iii) of the second method of the invention involves the determination of the concentration of the test analyte in the test sample by applying a correction factor to the concentration of the test analyte in the reference sample, said correction factor being the proportionality constant between the total intensity of the analyte in the test sample and the total intensity of the analyte in the reference sample i.e., m = Itest/Iref-

The term "proportionality constant", as used herein, relates to a ratio of peak intensities which, ideally should not be dependent on the background levels of the test analyte in the test sample or to the noise level.

Once the proportionality constant has been determined, the concentration of the test analyte in the reference sample can be determined by the formula:

Ctest ^{= m}^ref wherein C_test is the concentration of the analyte in the test sample, C_ref is the concentration corresponding to the analyte in the reference sample and m is the proportionality constant.

In a preferred embodiment, the mass spectrometry is carried out after fractionation of the test sample and of the reference sample. In a still more preferred embodiment, the fractionation is carried out by reverse phase chromatography.

COMPUTER-IMPLEMENTED MEANS

Computer implementation of different embodiments of the first and second method of the invention can be achieved using a computer program providing instructions in a computer readable form. The computer would collect the data, analyze the data as in accordance with the methods described herein, and then provide a result of the analysis. Thus, in another embodiment, the invention relates to a computer program or a computer-readable media containing means for carrying out a method of the invention. The computer implementation of the first method of the invention includes, without limitation, one or more of the following modules:

Control means for a mass spectrometer and, as the case may be, for separating the sample, so that mass spectra at a given m/z value and, as the case may be, at a given retention time, are collected. This module includes instructions for controlling a mass spectrometer including ionization and detection conditions. If the method involves a first fractionation step, the module may comprise additionally control means for the fractionation means. In the particular case that the fractionation is carried out by reverse phase chromatography, the module includes instructions for controlling column pressure, mobile phase composition, frequency of fraction collection and the like.

Means for determining the peak intensity of the analyte and of the naturally- occurring isotopologue thereof in the test sample and of the references samples. The module comprises means for performing integration of the peak areas corresponding to the test analyte and to the isotopologue in a given set of spectra. The module will preferably incorporate means for detecting the test analyte in a single peak or for integrating peaks of the same m/z value corresponding to a given retention time interval. The time interval where the integration is to be carried out can be inputted manually or, alternatively, can be determined by the program based on the comparison of the different spectra at different retention times. The module should preferably contain means for subtracting the background value from the peak intensities. Means for (iii) determining the concentration of M in the test sample by interpolating the peak intensity of M in the test sample within a calibration curve obtained from (a) the intensities of the peaks of M and of the at least one naturally-occurring isotopologue of M in the reference samples and (b) the concentrations of M and of the at least one naturally-occurring isotopologue of M in said reference samples.

The computer implementation of the second method invention includes, without limitation, one or more of the following modules: Control means for a mass spectrometer and, as the case may be, for separating the sample, so that mass spectra at a given m/z value and, as the case may be, at a given retention time are collected,

Means for determining the peak intensity of M in the test sample and of M in the at least one reference sample and

Means for determining the concentration of M in the test sample by applying a proportionality factor to the concentration of M in the reference sample, wherein said proportionality factor is the ratio of the peak intensities of M in the test sample and in the reference sample.

Different types of computer language can be used to provide instructions in a computer readable form. For example, the computer program can be written using languages such as C, C++, Microsoft C#, Microsoft Visual Basic, FORTRAN, PERL, HTML, JAVA, S, UNIX or LINUX shell command languages such as C shell script, and different dialects of such languages. "R," an S language dialect, is an example of a dialect with attributes facilitating analyses like those presented here (see http://cran.us.r-project.org).

Different types of computers can be used to run a program for performing analysis techniques described herein. Computer programs for performing analysis techniques described herein can be run on a computer having sufficient memory and processing capability. An example of a suitable computer is one having an Intel Pentium (g)-based processor of 200 MHZ or greater, with 64 MB or more main memory. Equivalent and superior computer systems are well known in the art.

Standard operating systems can be employed for different types of computers. Examples of operating systems for an Intel Pentium (2)-based processor includes the Microsoft Windows TM family such as Windows NT, Windows XP, and Windows 2000 and LINUX. Examples of operating systems for Apple computers include OSX, UNIX and LINUX operating systems. Other computers and their operating systems are well known in the art. In different embodiments, the R language is used on an Intel- based computer with 4GB ram dual 866 MHz Pentium m processors running the LINUX-operating system or an IBM computer running the AIX operating system with an Intel-based computer running the Windows NT or XP operating system as an x- windows terminal.

KITS OF THE INVENTION

In another embodiment, the invention provides a kit for the determination of the concentration of an analyte in a test sample comprising

(i) a reference sample of the same nature than the test sample and (ii) information as to the concentration of analyte in the test sample and as to the proportionality factor between the analyte and the peak intensity in the mass spectra.

Component (i) corresponds to a reference sample of the same nature than the test sample. The term "same nature" has been defined in detail in the context of the first method of the invention. Thus, if the test sample is serum, the reference sample is serum. If the test sample is urine, the reference sample is urine. Preferably, the reference sample corresponds to a normalized sample obtained by pooling samples from many different individuals.

Component (ii) contains the information needed for determining the concentration of the test metabolite in the test sample, namely, the concentration of test metabolite in the reference sample and the proportionality factor between the concentration of test metabolite and the peak intensity in the mass spectrum. These values are determined using any method known in the art but, preferably, they are determined using the first method of the invention.

In a preferred embodiment, the kit is suitable for use in a method wherein the sample is fractionated prior to its analysis by mass spectrometry, in which case the kit also contains information related to the retention time interval of the test analyte.

In a preferred embodiment, the reference sample is lyophilized. In this case, the sample is reconstituted prior to the determination. In additional embodiments, the kit of the invention further comprises one or more components selected from the group of

(i) a buffer or solvent solution for reconstituting the lyophilised reference sample, (ii) means for obtaining the biological sample,

(iii) a container for the test sample, (iv) a solution useful for extracting the test analyte from the biological sample,

(v) a reagent useful for removing proteins from the test sample, (vi) separation means for separating metabolites present in the reference sample,

(vii) information as to the m/z value of the test analyte and as to the retention time of the analyte in the separation means as defined in (ii), (viii) instructions as to how to use the kit

Component (i) comprises a buffer solution suitable for reconstituting the reference sample in case it is provided in the lyophilized form or for diluting the reference and the test samples to working concentrations. Suitable buffer systems may be found e.g., in Sambrook, J., et al, Molecular Cloning, A Laboratory Manual, 3rd edition, CSHL Press (2001) Cold Spring Harbor, N. Y. Preferred buffer substances are Tris-(hydroxymethyl)- aminomethane (TRIS), 2-morpholinoethanesulfonic acid (MES) phosphate, N-(2- Hydroxyethyl)piperazine-N'-(2-ethanesulfonic acid) (HEPES), acetate, salts thereof, and other suitable substances.

Component (ii) relates to means for obtaining the test sample and may comprise a syringe, a micro catheter, an endoscope, a toothpick, a brush, a needle, a lancet, a swab, a cup, a spatula, a biopsy gun, a cotton bud and the like.

Component (iii) of the kit of the invention can also comprise tubes for sample collection. In a preferred embodiment, the sample is blood and/or plasma, where the tubes for blood collection are operated manually or by vacuum. Depending on the intended type of sample, the kit may contain anticoagulants, low molecular weight heparin, citrate, EDTA, Hirudin, Draculin and other anticoagulants. Alternatively if serum is intended as test sample, the kit may contain clot activators such as factor X activators, and/or glass pearls or other structures to increase the surface thereby facilitating and enhancing the clotting process.

Component (iv) includes reagents useful for extracting the test metabolite from the biological sample. Suitable reagents for this purpose include, without limitation, organic solvents and mixtures thereof with water, charcoal and the like.

Component (v) includes deproteinizing reagents such as perchloric acid (HClO₄), acetonitrile, trichloroacetic acid, sulfo salicylic acid and the like.

Component (vi) includes separation means for separating metabolites present in the reference sample. Suitable separation means include without limitation, chromatographic columns, isoelectrofocusing and electrophoretic gels.

According to one additional embodiment, the package can comprise a box, and a wrapper enveloping the box. The package can be hermetically sealed. The package can be wrapped in shrink wrap.

Component (vii) information as to the m/z value of the test analyte and as to the retention time of the analyte in the separation means as defined in (ii).

Component (viii) comprises instructions as to how to use the kit. According to various embodiments, the kit can further comprise information in electronic or paper form. The information can comprise, for example, instructions for measuring the level of the analyte of interest.

Components (vii) and (viii) contain informative material than can be provided in printed form or, alternatively, can be provided in a computer readable media such as magnetic disks, tapes and the like), optical media (CD-ROM, DVD) and the like. The media can additionally or alternatively contain Internet websites providing said instructions. In further aspects, the invention relates to a kit for the determination of the concentration of an analyte in a test sample comprising

(i) a reference sample of the same nature than the test sample and (ii) information as to the concentration of analyte in the test sample and as to the proportionality factor between the concentration of analyte and the peak intensity in the mass spectra.

In a preferred embodiment, component (ii) of the kit further comprises information as to the retention time interval of the analyte.

In a preferred embodiment, the kit contains a reference sample is lyophilized.

In a still more preferred embodiment, the kit further comprising one or more of a component selected from the group of (i) a buffer solution for reconstituting the lyophilised reference sample,

(ii) means for obtaining the biological sample, (iii) a container for the test sample, (iv) a solution useful for extracting the test analyte from the biological sample, (v) a reagent useful for removing proteins from the test sample,

(vi) separation means for separating metabolites present in the reference sample,

(vii) information as to the m/z value of the test analyte and as to the retention time of the analyte in the separation means as defined in (ii),

(viii) instructions as to how to use the kit.

DIAGNOSTICS ASSAYS

The analytical techniques described herein can be used in performing diagnostic analysis. Diagnostic analysis can be performed by measuring the presence or amount of a marker associated with a disease or disorder. A marker can be based on a single or multiple analytes. The determination of the concentration of a given analyte in a sample may be suitable for determining (1) the presence or level of a disease or disorder; (2) the possibility of contracting a disease or disorder, (3) the probability of response to a given therapy. Different types of markers can be measured to determine whether an association exists including markers attributed to a causative agent, markers directly involved in disease and disorder, and/or markers reflecting a disease or disorder state.

The analytical techniques described herein are also suitable for the evaluation of compound pharmacology. For this purpose, the concentration of a given compound or of the metabolites thereof can be determined at different time points after the compound as been administered. Metabolic studies include the determination by sampling of biological materials the absorption, distribution, metabolism, and excretion of a compound and its metabolic by-products. Such evaluations have a variety of different uses including identifying important therapeutic targets, prioritizing potentially therapeutic compounds, identifying toxic metabolites, identifying therapeutic metabolites, identifying increased or decreased production of analytes that may harm a cell or animal and identifying increased or decreased production of analytes providing a beneficial effect to a cell or organism.

Compound reverse pharmacology can be performed using compounds with known effects to determine new therapeutic targets or new uses for one or more known compounds. Such studies could involve the identification of biomarkers for an unintended effect, beneficial or not, of a therapeutic intervention.

Moreover, the methods of the invention are also suitable for the evaluation of a disease treatment since the_expression state of biomarkers provides information on the health of a cell or animal. Changes in the biomarker levels can be used to select particular treatments and to monitor treatment efficacy. The changes can be, for example, with respect to an untreated subject, different subjects at different states of treatment, or a subject at different times during treatment.

Other applications of the methods of the invention can be envisaged such as monitoring of contaminants in wet baths employed in clean rooms in the semiconductor industry, environmental, pharmaceutical, biotechnology, food processing, chemical manufacture and production of reagents and standards.

The invention is described hereinafter by the following examples which are to be construed as merely illustrative and not limitative of the scope of the invention.

EXAMPLES

EXAMPLE 1

1. First Phase

Solutions in methanol of groups of five selected metabolites at 10 μM concentration are prepared. The UPLC-MS experiment is designed to alternate the injection of samples of those solutions and methanol blanks. Each group is injected a total of three times.

1.1. Chromatographic method

The chromatographic separation is carried out on a reverse phase UPLC Acquity column BEH-C 18 100^χ2.1 mm from Waters Corporation. The volume injection is 2.5 μL and the total run time is ten minutes using a flow rate of 100 μL/min. The elution buffers are methanol (A) and a 999:1 (v/v) mixture of water and formic acid (B).

The column is eluted with a constant mixture A/B 95:5 in volume during 0.5 minutes, followed by a linear gradient during 1.0 minute to reach a mixture A/B 20:80 in volume. It follows another linear gradient during 3.5 minutes to reach an eluent containing exclusively B, which is passed during 2.5 minutes. Finally, a new gradient is applied during 0.2 minutes to return to a mixture A/B 95:5 in volume. This mixture ratio is kept for 2.3 minutes before the next injection.

1.2. Spectrometric method The injection into the electrospray ionization source takes place via the analyte probe. A splitter-stainless steel cross with a inner bore of 0.15 mm from Valco (reference JV1X.5XCS6) is set up between the UPLC post-column capillary and the stainless steel capillary of the analyte probe to infuse 100 μL/min methanol and to reduce the incoming total volume from 200 to approximately 5 μL/min.

The spectra are recorded in a centroid data format mode. The instrument operates in positive ion mode using W optics in a range of masses from 50 to 1000 Daltons. The ionization is achieved using 523 K as capillary temperature and 373 K as source temperature. The capillary voltage is set at 3000 V and the cone at 0 V. The desolvation gas flow is fixed at 500 L/min and the cone gas flow at 50 L/min.

1.3. Data compilation

The collected data is analyzed using the implanted software MassLynx (Waters Corporation, Milford, MA). Once the metabolite is identified by its m/z ratio, the maximum in its chromatographic retention time is recorded. The chromatographic peak is integrated, and the total intensity collected. A proportionality factor obtained from the division of the total intensity by the concentration is calculated. Any particularity observed is also carefully annotated.

2. Second phase

During this phase the metabolite is identified in a human plasma reference sample using the retention time and m/z ratio obtained in the first phase.

2.1. Plasma Sample

The human plasma used as reference sample is averaged human plasma obtained from 1.500 different healthy individuals, i.e., one single flask from Sigma Human Plasma

(reference P9523-5 mL), and it needs to be processed previous its analysis. It is obtained lyophilized from the provider, and LC-MS grade water (Sigma Chromasolv grade) is added according the provider specifications for its storage, forming this way a stock solution that MD Renal keeps at 193 K.

This plasma is processed before analysis to remove plasma proteins. This way, a sample of 100 μL of the stock solution is thawed in an ice bath and 900 μL of methanol (Sigma Chromasolv grade) are added. The mixture is vortexed during 2 min, centrifuged at 13000 rpm for 30 min and finally filtered using polypropylene 0.2 mm syringe filters from Teknokroma. The supernatant containing the targeted metabolites is then ready to be use as reference sample in the analysis protocol.

After the identification of the metabolites in the human plasma and their information has been collected in the first phase, solutions in plasma of groups of five selected metabolites at eight different concentrations are prepared. The concentration set consists in the addition of 0.1, 0.5, 1.0, 4.0, 6.0, 8.0 and 10.0 times the estimated concentration of metabolite to the plasma sample in a relation 1/1 in volume. The UPLC-MS experiment is designed alternating the injection of all groups of samples and methanol blanks, defining a series. Each series is injected a total of three times. The UPLC-MS experimental conditions are maintained as presented in the first phase.

Notice that the concentration obtained for the metabolite using this method is twenty times smaller than that in human plasma due to the dilution process, so a correction is applied.

2.2. Determination of metabolite concentration

The collected data is analyzed using an ad hoc tool after the *.raw files provided by MassLynx (Waters Coporation, Milford, MA) are converted into *.mzXML files using MassWolf (Seattle Proteome Centre/Institute for Systems Biology, Seattle, WA). The metabolite m/z ratio is automatically identified and all the integrated intensities of it in the three series annotated. The required calculations for the determination of the concentration of the metabolite in the human plasma sample are done by the software tool. The calculus of a metabolite concentration in the test sample using MS signal intensities is achieved by linear regression. A calibration curve obtained measuring the respective MS intensity signals at different metabolite concentrations as explain above.

Linearity between concentration and signal intensity is assumed in MD Renal protocols, and metabolite concentrations affecting that linearity are avoided. The capacity of the software tool to calculate the metabolite concentration by interpolation is therefore restricted to a range clearly indicated in the software.

A metabolite concentration (C₀) in the test sample can be interpolated by linear regression measuring the change in the metabolite MS intensity signal (I₁) after adding different well-known amounts of the same metabolite (X₁) to the reference samples.

The following process allows the calculation of the slope (m) l_o 771L_O T l_noi_se

I₁ = m(C_o + X₁) + I_noise

I₁ - I₀ = m(C_o + X₁) + I_noise - (mC_o + I_noise)

AI₁ = mX_i ; m = ^

As expected, m is dependent of the X₁, and not of C₀ or the noise level. Finally, the knowledge of the slope permits the direct calculation of C₀.

„ O 'noise

^L° ^~ m

The use of the isotopologue M* -representing in this example M+l- in the fitting allows interpolate the value of C₀, avoiding the difficulties of an extrapolation. The values obtained from M* can join the values from the M in the calculation of m considering AI₁- = I₁- - I^* X₁- = (M^* Percentage) x X₁

The lower limit for the reliability in the calculation of a metabolite concentration in our client's plasma sample is independent of the concentrations values used for the determination of C₀. In principle there is no limit since the entire MS methodology is based on the linear relation C α /(I). Based only on the interpolation, the lower limit will be defined by the concentration of the naturally occurring isotopologue.

2.3. Method validation

The metabolites concentration in the test sample determined by linear regression can be validated using isotopically labeled internal standards. Isotopically labeled metabolites are exogenous, meaning they are not naturally present in the human plasma. Most interesting, they possess the same physic-chemical properties of their natural equivalents in the plasma, and therefore their behavior is assumed to be identical to their endogenous equals. However, having a different mass they can be distinguished from the equivalent by their mass/charge ratio in a mass spectrometric spectrum.

Using the previously calculated concentration of metabolite in plasma, the concentration of an isotopically labeled metabolite added to the test sample can be established. The deviation from its well-known concentration determines the validity of the method.

To perform the validation trial, a well-known amount of isotopically labeled metabolite is added to the test sample. Its concentration can be directly calculated using the equation

C_L = C₀ ^

¹O where

C_L = Concentration of the labeled metabolite C₀ = Concentration of the test metabolite to validate I_L = Intensity of the labeled metabolite

I₀ = Intensity of the test metabolite to validate MDRenal performs three test experiments at different concentrations for certain number of metabolites in order to guarantee the reliability of our methodology.

3. Third phase

This phase considers the determination of the metabolite concentrations in the reference sample.

3.1. Sample preparation

The reference sample is averaged human plasma obtained from a large number of different healthy individuals, e.g., a mixture of four flasks from different lots of Sigma Human Plasma (reference P9523-5mL) containing plasma from 1.500 different individuals.

The plasma is obtained lyophilized from the provider. For its storage, LC-MS grade water (Sigma Chromasolv grade) is added according the provider specifications and the stock solution formed kept at 193 Kelvins.

When needed, this plasma is processed before analysis to remove plasma proteins. This way, a sample of 100 μL of the stock solution is thaw in an ice bath and 900 μL of methanol (Sigma Chromasolv grade) are added. The mixture is vortex during 2 min, centrifuge at 13000 rpm for 30 min and finally filtered using polypropylene 0.2 μm syringe filters from Teknokroma. The supernatant containing the targeted metabolites is then ready to be use as reference sample in the analysis protocol.

3.2. Determination of metabolite concentration

The protocol followed in this phase is coincident with the one from the second phase. However, only one single metabolite will be consider by experiment and the concentration set will be adjusted to a range of ten times the concentration obtained previously. EXAMPLE 2

Metabolite information in the Software

1. Basic principles

The software provided in the kit will automatically calculate hundreds of metabolite concentrations from individual plasma samples. At the same time, the software will be able to produce a set of statistical studies and provide the user an overview of the metabolite functions within the metabolome.

For every metabolite a specific data set is generated consisting of mass/charge ratio, isotopic distribution, expected retention time when pre-fractioning of the sample is considered, concentration in reference sample, range of linearity, and didactic general information of every metabolite. For the quantification of a particular metabolite by the analysis software a proprietary data file is required. This data file includes the mass/charge ratio for metabolite and its heavier isotopologue, isotopic distribution, expected retention time when pre-fractioning of the sample is considered and concentration in the reference sample for each metabolite analyzed. It will also include the uncertainty in the concentration value and a range of linearity.

2. Generic information

The information on every metabolite contained in the software encloses a graphical representation of its chemical structure according to the IUPAC Recommendations, the empirical formula, a text commenting the relevance of the metabolite, an average concentration range obtained from different sources (KEGG database, Human Metabolome database) and significant bibliography.

EXAMPLE 3

Quantification protocol

Spectral data processing The software tools used in the method of the invention are based in the same principles when selecting a spectral signals and adding their intensity in time. Herein it is defined the common steps in the data processing once the spectra have been converted to *.mzXML format.

A group of exogenous analytes (A) is added continuously post-column in all cases for providing a permanent set of signals to be used in the normalization of the spectra.

Getting Required Information The localization, identification and integration of metabolite signals in any kind of sample require some data to be previously provided by MD Renal. It is summarized in the following points:

1. The time interval (t_ls t₂) where the metabolite signal is expected.

2. External analyte m/z (A) expected. 3. Deviation δA accepted to recognize a peak as valid.

4. Metabolite m/z (M) expected.

5. Deviation δM' accepted to recognize a peak as valid.

6. Heavier metabolite isotopologue m/z (M+l) expected.

7. Deviation δ(M+l)' accepted to recognize a peak as valid. 8. Theoretical intensity proportion I_(M+I)/M expected.

9. Deviation δ I(M+I)/M accepted.

All these data could be summarized in an MS Excel table containing the information for all metabolites under examination.

Data Handling

To recognize a signal as belonging to certain metabolite and integrate its intensity later on in time requires several steps in every spectrum and a posterior treatment for all the spectra within the chromatographic time interval chosen.

For every spectrum within the time interval (t_ls t₂):

1. Assign the exact m/z value (A) to the larger signal contained within the interval (A-δA, A + δA).

2. Add all the m/z signal intensities (I_A) for A. 3. Calculate

M^' = |A - M|

4. Assign the exact m/z value (M) to all the signals contained within the interval (M'-δM', M'+δM').

5. Add all the m/z signal intensities (Imeasured) for M.

> 6. Add all the m/z signal intensities (I_nOise) within the interval (M'-δM', M'+δM') in the previous blank spectrum. 7. Assign a value I_M using the following equations wherein if is the m/z signal intensity for A in a blank sample,

8. Repeat 1.3 to 1.7 for (M+l) the same way it has been done for M. For all the spectra within the time interval (t_{l s} t₂):

9. Normalized total intensity signal for M.

Add all IM for the spectra where I(M+I)/IM is within the accepted interval ((I(M+I/ I M) - δ(I(M+i)/I M), (I(M+I)/ I M) - δ (I(M+I/ I M))-

IM ⁼ } IM

10. Normalized total intensity signal for (M+l).

Add all I(M+I) for the spectra considering only those where I(M+I) /IM is within the accepted interval ((I(M+I/ I M) - δ(I_(M+i)/ 1 M), (I(M+I/ I M) - δ(I_(M+i)/ I M)).

+ l)

The software calculates the metabolite concentration in a test sample (TS) exploiting the linearity existing between the ionized metabolite signal intensity and its concentration in solution. It uses reference samples (RS) where well-known amounts of the same metabolite have been added, and takes advantage of the fact that that linearity also applies to their increments according to the equations

I = mC + I₀ ; ΔI = mΔC + F_x The experiment contains three different kinds of samples, i.e, test (TS), reference (RS), and blank samples (BS). The experimental setup will consist in a series repeated three times. The series will follow the order:

BS, TS, BS, RSi, BS, RS₂, BS, RS₃, BS, RS₄, BS, RS₅, BS, RS₆, BS, RS₇, BS, RS₈, cleaning

A stepwise description of the process once the intensities have been obtained for all the samples is as follows:

Getting Required Information

1. Ask for the number (n, commonly 8) of RS.

2. Ask for the metabolite concentration added to each sample (C_add).

3. Process data as described in "Spectral Data Processing" and obtain the normalized total intensities values IM and I(M+I> in TS and all RS.

Data Handling

1. Calculate the absolute concentration of the isotopologue (M+l) added to every RS using

Cadd ⁼ I(M+l)/MC_add

(Notice that the equation uses the theoretical intensity proportion I_(M+I/ I _M). 2. Make the subtractions for all n samples of the three series

AI_n = IM RSn - IM TS ^ar*d ΔI_n = I(M+I) RSΠ ^~ I(M+I) TS Notice that IM T_S and I(M+I> T_S must correspond to the ones obtained from the TS of the same series.

3. Perform the following Linear Regression for each one of the three series. They should include all the values obtained, i.e. ΔI_n and ΔI_n* versus C_add and C_add* considering all RS and TS (ΔC=0).

ΔI_π = mC_add + F_x'

4. Provide the measuring system factor (F_x) for the three of them.

F_X = I_A X F_X'

5. Provide the determination coefficient (R²) for the linear regressions performed.

Concentration Determination 1. Calculate the metabolite concentration in TS for each series using the equation r _ ^M TS

^{Cτs "} ^T

2. Provide average final concentration for the metabolite in plasma (C_TS)

3. Calculate the absolute concentration of metabolite (M) in every CS

4. Calculate the absolute concentration of the isotopologue (M+l) in every RS

CRS = I(M+1)/M CTS ⁺ ^add (Notice that the equation uses the theoretical intensity proportion I_(M+I)/M).

5. Show a graphic I versus C (C_RS and C_RS*) using the normalized total intensity values IM and I(M+I> and mark the point for (I_M T_S, CTS) for its easier identification.

I = mC + I₀

(Notice that the graphic should include all the samples of the three series)

A second software tool makes use of a reference sample (RS) where the metabolites concentration is known for determining the metabolites concentration in Customer Samples (CS). It is based on the comparison between MS intensity signals of the metabolites in CS and those of the metabolites in RS. Notice that the herein named

"reference sample" refers to the previously named "test sample" in this example. At this stage the concentration of the test analyte in this sample is already known, becoming the "reference sample".

The experiment contains three different kinds of samples, i.e, reference (RS), customer (CS), and blank samples (BS). The experimental setup will consist in a series. The series order is defined depending on the experimental requirements. For example, it could follow the order:

BS, RS, BS, CSi, CS₂, CS3, CS4, CS5, BS, RS, BS, CS₆, CS₇, CSs, CS9, CS10, BS, RS, BS, CSn, CSi₂, CSi₃, CSi₄, CSi₅, BS, and so on...

A stepwise description of the process is as follows: Getting Required Information

The information required depends on the method used in the calculations

1. Ask for the number (n) of Customer Samples (CS).

2. Ask for the Measuring System Factor (F_x). 3. Ask for the metabolite concentration (C_{M RS}) in the Reference Sample (RS)

Data Handling

1. Process data as described in "Spectral Data Processing" and obtain the normalized total intensities values I_M in RS and all CS.

Concentration Determination

The metabolites concentration in every one of the n CS will be calculated by comparison of its I_{M CS} with I_{M RS}- AS the concentration in the reference sample (C_RS) is known and provided by MD Renal, the concentration of the metabolite in the Customer sample (Ccs) will be calculated straightforward as follows:

_ ¹M CS_n

-M CS J_nj-_j ^{~~ L} ~Mm R IYS₁J ~ wJ r_x

¹M RS

EXAMPLE 4

Method Validation

It is intended to perform validation tests for selected metabolites. For this purpose, the software includes a processing tool for the calculation of the metabolite concentrations in a particular customer sample using internal standards. Comparing the results from this methodology with those obtained using a reference sample will test the reliability of the final product.

Data processing will depend on the internal standard chosen, since signal overlapping with the metabolite under examination could occur. This way, there are two different equations covering both possibilities.

1.1. No Signal Overlapping Getting Required Information

1. Ask for the metabolite to examine (M).

2. Ask for the internal standard to use (L). 3. Ask for the internal standard concentration in CS (C_{L CS}).

Data Handling

1. Process data as described in "Spectral data Processing" and obtain the normalized total intensity values for M (IM C_S) and L (IL C_S) in all the CS under validation.

Concentration Determination

The following equation will calculate the concentration (C_{M CS}) of the target metabolite. r _ _r IM cs

^LM CS — ^LL CS ^"J

¹L CS

1. Provided C_{M CS} value calculated for comparison to that obtained by the external analyte protocol.

1.2. Signal Overlapping

The equation calculates the concentration of a metabolite presents in a customer sample (CM CS) using the ratio of two MS signal intensities (Res) and comparing it to the corresponding one (R_RS) in RS.

The design of this equation requires that the intensity ratio (K=XJY) between two common signals (x,y) to be different for the metabolite (R_M) and the internal standard (RL). Getting Required Information

The localization, identification and integration of metabolite signals require some data to be previously provided by MD Renal. They are summarized in the following points: 1. The time interval (t_ls t₂) where the metabolite signal is expected.

2. Concentration of the metabolite in the RS (C_{M RS}).

3. Concentration of the internal standard in the RS (C_{L RS}).

4. Concentration of the internal standard in CS (C_{L CS}). 5. First m/z (x) expected.

6. Second m/z (y) expected.

7. Theoretical metabolite intensity ratio (R_M).

8. Theoretical internal standard intensity ratio (R_L)-

9. Deviation δx accepted to recognize a peak as valid. 10. Deviation δy accepted to recognize a peak as valid.

Data Handling

1. Calculate the normalized total intensity values XR_S and YR_S and Xcs and Yes for m/z (x) and (y) as described for I_M in "Spectral Data Processing"

2. Perform the signals intensity ratios R_RS and Res

„ XRS , _ Xcs R_RS = ^- and R_cs = —

^Jf RS *CS Concentration Determination

The equation is as follows: r _ _r C_{L CS} (RL ^~~ Res) (RM ^~~ RRS) „ LM CS - ^LM RS T; T^ 5 TT^ 5 T^_x

^LL RS ^^KL ^{"" K}RSil^KM ^{"" K}CSJ

Provided C_{M CS} value calculated for comparison to that obtained by the generic protocol.

EXAMPLE 5

Determination of the concentration of threonine in a biological sample

1. Preparation of the reference samples

An extract of 1 mL of the test plasma mixture (450 healthy subjects, 1.5 mL/subject) obtained from Banco de Sangre de Guipύzcoa and stored at 203 K was thawed in an ice bath. In order to precipitate the plasma proteins in the extract, methanol in a 9/1 (v/v) ratio was added. The resulting solution was stirred by means of a Vortex for two minutes and centrifuged at 13000 rpm for 30 minutes. The supernatant was then collected and filtered using 0.2 μm filters. With this process the test plasma extract (TPE) is ready to be used.

This extract was mixed with methanol and with a stock solution (SS) of the metabolites threonine in methanol (100 μM, 50 mL) as is described in Table 1. A sample of the test plasma to be calibrated (TS) and a series of 8 reference samples (RS) were thus obtained.

With this process of dilutions, the concentration in the test to be calibrated (TS) is 20 times less than in relation to the untreated plasma.

Sample SS Volume Methanol TPE Volume [Metabolite]

TS 0 100 100 [TS]

RS₂ 5 95 100 [TS] + 2.5

RS₃ 10 90 100 [TS] + 5.0

RS₄ 20 80 100 [TS] + 10

RS₅ 70 30 100 [TS] + 35

RS₆ 80 20 100 [TS] + 40

RS₇ 90 10 100 [TS] + 45

RS₈ 100 0 100 [TS] + 50

Table 1. List of volumes (μL) added and final concentration (μM) of the metabolite threonine in the different samples.

The different samples were analyzed using UPLC-MS and further studied as described below.

2. Liquid chromatography (UPLC) The chromatographic separation was carried out in a Waters Acquity system. A BEH HILIC column (100x1 mm; 1.7 μm particle size) maintained at 313 K was used. The total time per chromatogram was 5 minutes.

A gradient of different ratios formed by a mixture A of acetonitrile and water -95/5 (v/v) + 0.2% formic acid- and another mixture B also of acetonitrile and water -40/60 (v/v) + 0.2% formic acid- was used as mobile phase in the experiments. The flow used was 250μL/min and the injection volume 2.5 μL. The evolution of the composition of the mixture during the chromatography can be seen in Table 2.

Time / mm A (%) B (%)

0 99 1

1.0 99 1

2.0 83 17

3.0 50 50

3.5 50 50

3.7 99 1

5.0 99 1

Table 2. Mobile phase gradient

3. Mass spectrometry (MS)

A PEEK cross (Teknokroma, UP-P729) with an inner diameter of 0.020" and a dead volume of 2.736 μL was installed between the Waters Acquity UPLC used in the chromatography and the Waters LCT Premier XE analyte probe. The cross allows incorporating a reference analyte (40 μM, 2.5 μL/min) to the complex mixture from the UPLC (250 μL/min) and reducing the inlet flow in the ionization source by means of electrospraying at 8.5 μL/min.

The LCT Premier XE was adjusted and calibrated to work in positive mode using a W arrangement for the flight tube and a mass range of 50 to 1000 Da. The ionization was done using a voltage of 3000 V and a temperature of 523 K in the capillary. The source was maintained at 373 K with a voltage in the entrance cone fixed at 15 V. The nitrogen flow used as desolvation gas was adjusted at 500 L/min and the cone flow to 50 L/min.

The mass spectra were recorded in centroid mode and with the Waters standard *.raw format.

4. Quantification

The recorded spectra were converted to *.mzXML format using MassWo If software. Once this was done, a software tool was used to quantify both metabolites in the reference plasma. The parameters used in the adjustment are shown in Table 3.

This software was developed by Seattle Proteome Center (Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103-8904) and released under GLPL (Lesser General Public License), that is, free software available to non-free software. It uses MassLynx libraries from Waters Corporation (Milford , MA) to convert *.raw directories into *.mzXML format files. In any case, any other software able to convert the *.raw data files from Waters to *.mzXML could be used.

Data was processed following the steps described in EXAMPLE 3 and using the information exposed in Table 3.

Threonine m/z Range

Analyte 443.2335 0.1

Metabolite (M) 120.0661 0.02

Isotopologue (M+ 1) 121.0691 0.02

Time range 2.0/2.8

Table 3. Parameters used in estimating the concentration of threonine. Notice that the analyte is used to normalize the peaks intensity between spectra. The analyte used in this experiment is rhodamine B in a final concentration of 12.5nM. The intensity values obtained for different concentrations of metabolite are shown in Table 4. The selected ion monitoring chromatograms of the different samples for the lighter isotopologue of threonine considered is shown in Figure 1 and for the heavier isotopologue in Figure 2. The mass spectrometric spectrum for this metabolite is shown in Figure 3.

Sample Series 1 Series 2 Series 3

TS(M) 11356.726 11595.816 11073.377

TS (M+1) 1459.947 1547.408 1491.523

RSi (M) 27833.284 28553.351 30830.108

RSi (M+1) 3683.764 3928.550 4294.591

RS₂(M) 48590.944 49334.221 51843.450

RS₂ (M+1) 6786.167 6564.866 6928.607

RS₃ (M) 97951.510 98954.688 97862.219

RS₃ (M+1) 13074.901 13307.549 13274.064

RS₄(M) 160156.960 148786.369 159965.979

RS₄(M+1) 20908.460 19732.443 20980.858

RS₅ (M) 165487.325 168545.549 181951.379

RS₅ (M+1) 21664.142 22258.296 23550.022

RS₆(M) 200075.480 196458.873 203789.871

RS₆(M+1) 25803.981 25447.981 26712.290

RS₇ (M) 224724.942 238046.940 224315.115

RS₇ (M+1) 28723.240 30383.315 28529.910

RS₈ (M) 245857.017 263676.795 268242.029

RS₈ (M+1) 31072.389 33271.395 33850.059

Table 4. Intensities obtained (cps) in estimating the concentration of threonine.

The concentrations in the different series were estimated from these results. The values obtained are shown in Table 5. Series 1 Series 2 Series 3

[Threonine] 5.01 5.53 5.42

Table 5. Values estimated for the concentration (μM) of threonine in three series.

These results allow estimating a concentration of 106.4 μM for the metabolite threonine in the reference plasma.

EXAMPLE 6

Determination of the concentration of tryptophan in a biological sample

1. Preparation of the reference samples

An extract of 1 mL of the test plasma mixture (450 healthy subjects, 1.5 mL/subject) obtained from Banco de Sangre de Guipuzcoa and stored at 203 K was thawed in an ice bath.

In order to precipitate the plasma proteins in the extract, methanol in a 9/1 (v/v) ratio was added. The resulting solution was stirred by means of a Vortex for two minutes and centrifuged at 13000 rpm for 30 minutes. The supernatant was then collected and filtered using 0.2 μm filters. With this process the test plasma extract (TPE) is ready to be used.

This extract was mixed with methanol and with a stock solution (SS) of the metabolite tryptophan in methanol (100 μM, 50 mL) as is described in Table 6. A sample of the test plasma to be calibrated (TS) and a series of 8 reference samples (RS) were thus obtained.

With this process of dilutions, the concentration in the test to be calibrated (TS) is 20 times less than in relation to the untreated plasma. Sample SS Volume Methanol TPE Volume [Metabolite]

TS 0 100 100 [TS]

RS₂ 5 95 100 [TS] + 2.5

RS₃ 10 90 100 [TS] + 5.0

RS₄ 20 80 100 [TS] + 10

RS₅ 70 30 100 [TS] + 35

RS₆ 80 20 100 [TS] + 40

RS₇ 90 10 100 [TS] + 45

RS₈ 100 0 100 [TS] + 50

Table 6. List of volumes (μL) added and final concentration (μM) of the metabolite in the different samples.

2. Liquid chromatography (UPLC)

The chromatographic separation was carried out in a Waters Acquity system. A BEH HILIC column (100x1 mm; 1.7 μm particle size) maintained at 313 K was used. The total time per chromatogram was 5 minutes.

A gradient of different ratios formed by a mixture A of acetonitrile and water -95/5 (v/v) + 0.2% formic acid- and another mixture B also of acetonitrile and water -40/60 (v/v) + 0.2% formic acid- was used as mobile phase in the experiments. The flow used was 250μL/min and the injection volume 2.5 μL. The evolution of the composition of the mixture during the chromatography can be seen in Table 7. Time / mtn A(%) B (%)

0 99 1

1.0 99 1

2.0 83 17

3.0 50 50

3.5 50 50

3.7 99 1

5.0 99 1

Table 7. Mobile phase gradient

3. Mass spectrometry (MS)

4. Quantification The recorded spectra were converted to *.mzXML format using MassWo If software. Once this was done, a software tool was used to quantify both metabolites in the reference plasma. The parameters used in the adjustment are shown in Table 3.

Data was processed following the steps described in EXAMPLE 3 using the information exposed in Table 8.

Tryptophan m/z Range

Analyte 443.2335 0.1

Metabolite (M) 205.0977 0.02

Isotopologue (M+ 1) 206.1008 0.02

Time range 1.6/2.5

Table 8. Parameters used in estimating the concentration of tryptophan. Notice that the analyte is used to normalize the peaks intensity between spectra. The analyte used in this experiment is rhodamine B in a final concentration of 12.5nM.

The intensity values obtained for different concentrations of metabolite are shown in Table 9. The selected ion monitoring chromatograms of the different samples for the lighter isotopologue of tryptophan considered is shown in Figure 4 and for the heavier isotopologue in Figure 5. The mass spectrometric spectrum for this metabolite is shown in Figure 6. Sample Series 1 Series 2 Series 3 TS (M) 11356.726 11595.816 11073.377 TS (M+ 1) 1279.620 1382.149 1341.726 RSi (M) 34970.417 36700.574 41582.320 RSi (M+ 1) 2082.697 1967.106 2341.771 RS₂ (M) 58479.641 56191.425 55612.783 RS₂ (M+ 1) 3225.444 3264.037 3135.919 RS₃ (M) 103129.138 102191.637 102548.641 RS₃ (M+ 1) 4961.291 4572.021 4926.045 RS₄ (M) 153118.192 139302.021 158555.288 RS₄ (M+ 1) 7464.449 6062.550 7415.038 RS₅ (M) 150096.000 156716.081 173162.455 RS₅ (M+ 1) 6942.638 7199.628 8210.207 RS₆ (M) 181024.398 180209.702 184993.583 RS₆ (M+ 1) 8132.581 8306.836 8721.117 RS₇ (M) 201300.631 218487.904 195637.371 RS₇ (M+ 1) 8720.369 9747.996 8616.971 RS₈ (M) 210072.542 229199.268 238884.612 RS₈ (M+ 1) 9162.376 9657.258 10533.260

Table 9. Intensities obtained (cps) in estimating the concentration of tryptophan.

The concentrations in the different series were estimated from these results. The values obtained are shown in Table 10.

Series 1 Series 2 Series 3

[Tryptophan] 2.40 2.37 2.23

Table 10. Values estimated for the concentration (μM) of tryptophan in three series.

These results allow estimating a concentration of 46.7 μM for the metabolite tryptophan in the reference plasma.

EXAMPLE 7 Determination of the concentration of L-methionine in a biological sample

1. Preparation of the reference samples

This extract was mixed with methanol and with a stock solution (SS) of the metabolite methionine in methanol (100 μM, 50 mL) as is described in Table 11. A sample of the test plasma to be calibrated (TS) and a series of 8 reference samples (RS) were thus obtained.

Sample SS Volume Methanol TPE Volume [Metabolite]

TS 0 100 100 [TS]

RS₂ 5 95 100 [TS] + 3.498

RS₃ 10 90 100 [TS] + 6.997

RS₄ 20 80 100 [TS] + 13.994

RS₅ 70 30 100 [TS] + 48.978

RS₆ 80 20 100 [TS] + 55.975

RS₇ 90 10 100 [TS] + 62.972

RS₈ 100 0 100 [TS] + 69.969

Table 11. List of volumes (μL) added and final concentration (μM) of the metabolite methionine in the different samples.

2. Liquid chromatography (UPLC)

A gradient of different ratios formed by a mixture A of acetonitrile and water -95/5 (v/v) + 0.2% formic acid- and another mixture B also of acetonitrile and water -40/60 (v/v) + 0.2% formic acid- was used as mobile phase in the experiments. The flow used was 250μL/min and the injection volume 2.5 μL. The evolution of the composition of the mixture during the chromatography can be seen in Table 12. Time / min A(%) B (%)

0 99 1

1.0 99 1

2.0 83 17

3.0 50 50

3.5 50 50

3.7 99 1

5.0 99 1

Table 12. Mobile phase gradient

3. Mass spectrometry (MS)

4. Quantification

The recorded spectra were converted to *.mzXML format using Mass Wo If software. Once this was done, a software tool was used to quantify both metabolites in the reference plasma. The parameters used in the adjustment are shown in Table 3. This software was developed by Seattle Proteome Center (Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103-8904) and released under GLPL (Lesser General Public License), that is, free software available to non-free software. It uses MassLynx libraries from Waters Corporation (Milford , MA) to convert *.raw directories into *.mzXML format files. In any case, any other software able to convert the *.raw data files from Waters to *.mzXML could be used.

Data was processed following the steps described in EXAMPLE 3 using the information exposed in Table 13.

Methionine m/z Range

Analyte 443.2335 0.1

Metabolite (M) 150.0589 0.01

Isotopologue (M+ 1) 151.0615 0.01

Time range 1.9/2.8

Table 13. Parameters used in estimating the concentration of methionine. Notice that the analyte is used to normalize the peaks intensity between spectra. The analyte used in this experiment is rhodamine B in a final concentration of 12.5nM.

The intensity values obtained for different concentrations of metabolite are shown in Table 14.

Sample Series 1 Series 2 Series 3 TS (M) 11356.726 11595.816 11073.377 TS (M+ 1) 1459.947 1547.408 1491.523 RSi (M) 27833.284 28553.351 30830.108 RSi (M+ 1) 3683.764 3928.550 4294.591 RS₂ (M) 48590.944 49334.221 51843.450 RS₂ (M+ 1) 6786.167 6564.866 6928.607 RS₃ (M) 97951.510 98954.688 97862.219 RS₃ (M+ 1) 13074.901 13307.549 13274.064 RS₄ (M) 160156.960 148786.369 159965.979 RS₄ (M+ 1) 20908.460 19732.443 20980.858 RS₅ (M) 165487.325 168545.549 181951.379 RS₅ (M+ 1) 21664.142 22258.296 23550.022 RS₆ (M) 200075.480 196458.873 203789.871 RS₆ (M+ 1) 25803.981 25447.981 26712.290 RS₇ (M) 224724.942 238046.940 224315.115 RS₇ (M+ 1) 28723.240 30383.315 28529.910 RS₈ (M) 245857.017 263676.795 268242.029 RS₈ (M+ 1) 31072.389 33271.395 33850.059

Table 14. Intensities obtained (cps) in estimating the concentration of methionine.

The concentrations in the different series were estimated from these results. The values obtained are shown in Table 15.

Series 1 Series 2 Series 3

[Methionine] 1.38 1.32 1.425

Table 15. Values estimated for the concentration (μM) of methionine in three series.

These results allow estimating a concentration of 27.5 μM for the metabolites methionine in the reference plasma.

EXAMPLE 8 Determination of the concentration of cis-4-hydroxyproline in a biological sample

5. Preparation of the reference samples

This extract was mixed with methanol and with a stock solution (SS) of the metabolite cis-4-hydroxyproline in methanol (100 μM, 50 mL) as is described in Table 16. A sample of the test plasma to be calibrated (TS) and a series of 8 reference samples (RS) were thus obtained.

Sample SS Volume Methanol TPE Volume [Metabolite]

TS 0 100 100 [TS]

RS₂ 5 95 100 [TS] +1.937

RS₃ 10 90 100 [TS] + 3.874

RS₄ 20 80 100 [TS] + 7.748

RS₅ 70 30 100 [TS] + 27.118

RS₆ 80 20 100 [TS] + 30.992

RS₇ 90 10 100 [TS] + 34.866

RS₈ 100 0 100 [TS] + 38.740

Table 16. List of volumes (μL) added and final concentration (μM) of the metabolite cis-4- hydroxyproline in the different samples.

6. Liquid chromatography (UPLC)

A gradient of different ratios formed by a mixture A of acetonitrile and water -95/5 (v/v) + 0.2% formic acid- and another mixture B also of acetonitrile and water -40/60 (v/v) + 0.2% formic acid- was used as mobile phase in the experiments. The flow used was 250μL/min and the injection volume 2.5 μL. The evolution of the composition of the mixture during the chromatography can be seen in Table 17. Time / min A(%) B (%)

0 99 1

1.0 99 1

2.0 83 17

3.0 50 50

3.5 50 50

3.7 99 1

5.0 99 1

Table 17. Mobile phase gradient

7. Mass spectrometry (MS)

8. Quantification

The recorded spectra were converted to *.mzXML format using MassWo If software. Once this was done, a software tool was used to quantify both metabolites in the reference plasma. The parameters used in the adjustment are shown in Table 3. This software was developed by Seattle Proteome Center (Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103-8904) and released under GLPL (Lesser General Public License), that is, free software available to non-free software. It uses MassLynx libraries from Waters Corporation (Milford , MA) to convert *.raw directories into *.mzXML format files. In any case, any other software able to convert the *.raw data files from Waters to *.mzXML could be used.

Data was processed following the steps described in EXAMPLE 3 using the information exposed in Table 18.

cis-4-hydroxypro line m/z Range

Analyte 443.2335 0.1

Metabolite (M) 132.0661 0.01

Isotopologue (M+ 1) 133.0691 0.01

Time range 2.5/3.5

Table 18. Parameters used in estimating the concentration of cis-4-hydroxyproline. Notice that the analyte is used to normalize the peaks intensity between spectra. The analyte used in this experiment is rhodamine B in a final concentration of 12.5nM.

The intensity values obtained for different concentrations of metabolite are shown in Table 19.

Sample Series 1 Series 2 Series 3 TS (M)

1974,470 1554,845 1394,721 TS (M+ 1) 2624,809 2338,020 2140,211 RSi (M) 2953,864 2817,516 2826,488 RSi (M+ 1) 2436,146 2337,403 2438,778 RS₂ (M) 5878,899 6439,076 6227,029 RS₂ (M+ 1) 2569,644 2672,400 2652,236 RS₃ (M) 10766,847 10868,348 10669,463 RS₃ (M+ 1) 3031,707 3007,169 3062,163 RS₄ (M) 19359,535 19392,111 19668,558 RS₄ (M+ 1) 3680,447 3610,752 3506,113 RS₅ (M) 65464,930 64140,483 60267,810 RS₅ (M+ 1) 6561,464 6402,988 6100,790 RS₆ (M)

74135,609 73138,861 70371,808 RS₆ (M+ 1) 6910,627 6924,493 6693,103 RS₇ (M) 78824,343 78519,852 77407,145 RS₇ (M+ 1) 7355,142 7391,171 7244,652 RS₈ (M) 86906,896 84939,522 83246,285 RS₈ (M+ 1) 7703,798 7558,107 7543,517

Table 19. Intensities obtained (cps) in estimating the concentration of cis-4- hydroxyproline.

The concentrations in the different series were estimated from these results. The values obtained are shown in Table 20.

Series 1 Series 2 Series 3

[cis-4-hydroxypro line] 0.766 0.642 0.628

Table 20. Values estimated for the concentration (μM) of cis-4-hydroxyproline in three series.

These results allow estimating a concentration of 13.6 μM for the metabolite cis-4- hydroxyproline in the reference plasma.

EXAMPLE 9 Determination of the concentration of caffeine in a biological sample

1. Preparation of the reference samples

This extract was mixed with methanol and with a stock solution (SS) of the metabolite cis-4-hydroxyproline in methanol (100 μM, 50 mL) as is described in Table 21. A sample of the test plasma to be calibrated (TS) and a series of 8 reference samples (RS) were thus obtained.

Sample SS Volume Methanol TPE Volume [Metabolite]

TS 0 100 100 [TS]

RS₂ 5 95 100 [TS] +1.895

RS₃ 10 90 100 [TS] + 3.790

RS₄ 20 80 100 [TS] + 7.580

RS₅ 70 30 100 [TS] + 26.531

RS₆ 80 20 100 [TS] + 30.321

RS₇ 90 10 100 [TS] + 34.111

RS₈ 100 0 100 [TS] + 37.901

Table 21. List of volumes (μL) added and final concentration (μM) of the metabolite caffeine in the different samples.

2. Liquid chromatography (UPLC)

A gradient of different ratios formed by a mixture A of acetonitrile and water -95/5 (v/v) + 0.2% formic acid- and another mixture B also of acetonitrile and water -40/60 (v/v) + 0.2% formic acid- was used as mobile phase in the experiments. The flow used was 250μL/min and the injection volume 2.5 μL. The evolution of the composition of the mixture during the chromatography can be seen in Table 22. Time / min A(%) B (%)

0 99 1

1.0 99 1

2.0 83 17

3.0 50 50

3.5 50 50

3.7 99 1

5.0 99 1

Table 22. Mobile phase gradient

3. Mass spectrometry (MS)

4. Quantification

Data was processed following the steps described in EXAMPLE 3 using the information exposed in Table 23.

caffeine m/z Range

Analyte 443.2335 0.1

Metabolite (M) 195.0882 0.01

Isotopologue (M+ 1) 196.0907 0.01

Time range 0.35/0.95

Table 23. Parameters used in estimating the concentration of caffeine. Notice that the analyte is used to normalize the peaks intensity between spectra. The analyte used in this experiment is rhodamine B in a final concentration of 12.5nM.

The intensity values obtained for different concentrations of metabolite are shown in Table 24.

Sample Series 1 Series 2 Series 3 TS (M) 842,892 806,829 749,086 TS (M+ 1)

28,219 70,985 61,340 RSi (M) 1147,872 1056,967 1054,430 RSi (M+ 1) 91,828 110,339 122,212 RS₂ (M)

2747,665 2770,483 2829,817 RS₂ (M+ 1) 241,174 258,385 241,641 RS₃ (M) 5733,134 5544,656 5497,551 RS₃ (M+ 1)

605,560 572,938 573,558 RS₄ (M) 10120,377 9856,220 9852,231 RS₄ (M+ 1)

951,303 1005,434 998,640 RS₅ (M) 32252,828 32035,697 31958,101 RS₅ (M+ 1)

3130,013 3121,695 3087,293 RS₆ (M)

38080,726 36969,947 37521,386 RS₆ (M+ 1)

3550,013 3421,169 3443,449 RS₇ (M) 42754,752 40158,660 41016,462 RS₇ (M+ 1)

4021,046 3720,164 3856,592 RS₈ (M) 46452,147 44038,424 44751,907 RS₈ (M+ 1) 4231,822 4279,392 4240,140 ϊά (CΌS) in estimatin 2 the concentration ofcaffeine.

The concentrations in the different series were estimated from these results. The values obtained are shown in Table 25.

Series 1 Series 2 Series 3

[caffeine] 0.675 0.656 0.605

Table 25. Values estimated for the concentration (μM) of caffeine in three series.

These results allow estimating a concentration of 12.9 μM for the metabolite caffeine in the reference plasma.

Claims

1. A method for determining the concentration of a metabolite (M) of known m/z in a test sample by mass spectrometry which comprises the steps of: (i) performing mass spectrometry on the test sample and in at least two reference samples of the same nature as the test sample to which known and different amounts of M have been previously added,

(ii) determining the peak intensity of M in the spectra obtained from the test sample and of M and of at least one naturally-occurring isotopologue of M in the spectra obtained from the reference samples and

(iii) determining the concentration of M in the test sample by interpolating the peak intensity of M in the test sample within a calibration curve obtained from (a) the intensities of the peaks of M and of the at least one naturally-occurring isotopologue of M in the reference samples and (b) the concentrations of M and of the at least one naturally-occurring isotopologue of M in said reference samples.

2. A method as defined in claim 1 wherein said calibration curve is obtained by linear regression analysis.

3. A method as defined in claims 1 or 2 wherein the test sample and the reference samples are fractionated prior to the mass spectrometry, in which case the mass spectrometry is carried out on one or several pooled fractions obtained at a retention time or times which is/are suspected to contain the metabolite and the naturally-occurring isotopologue.

4. A method as defined in claim 3 wherein the fractionation is carried out by reverse phase chromatography or by normal-phase chromatography.

5. A method as defined in claim 4 wherein the peak intensities of M and/or of the at least one naturally-occurring isotopologue of M in each sample are determined in step (ii) by integration of the peak intensities within a retention time interval, wherein said interval is determined using a known analyte of known m/z present in a continuous mode within the retention time interval of M.

6. A method as defined in claim 5 wherein the time interval in which the integration is to be carried out is determined using the retention time of M and the naturally occurring isotopologue of M in the most concentrated of the reference samples.

7. A method as defined in claim 6 wherein the integrated signal intensity of M or of M and the naturally occurring isotopologue of M are normalized by dividing them by the integrated signal intensity of a known analyte within the retention time interval of M.

8. A method for the determination of the concentration of a metabolite (M) in a test sample by mass spectrometry comprising the steps of (i) performing mass spectrometry on the test sample and in at least one reference sample of the same nature than the test sample wherein said at least one reference sample contains a known concentration of M, (ii) determining the peak intensity of M in the test sample and of M in the at least one reference sample and

9. A method as defined in claim 8 wherein the test sample and the at least one reference sample are fractionated prior to the mass spectrometry, in which case the mass spectrometry is carried out on one or several pooled fractions obtained at a retention time or times which is/are suspected to contain the metabolite and the naturally-occurring isotopologue.

10. A method as defined in claim 9 wherein the fractionation is carried out by reverse- phase chromatography or normal-phase chromatography.

11. A method as defined in claim 10 wherein the peak intensities of M and/or of the at least one naturally-occurring isotopologue of M in each sample are determined in step (ii) by integration of the peak intensities within a retention time interval, wherein said interval is determined using a known analyte of known m/z present in a continuous mode within the retention time interval of M.

12. A method as defined in claim 11 wherein the time interval in which the retention time interval in which the integration is to be carried out is determined using the retention time of M in the most concentrated of the reference samples.

13. A method as defined in any of claims 1 to 12 wherein the sample is a biological sample.

14. A method as defined in claim 13 wherein the biological sample is a biofluid, preferably a urine or a plasma sample.

15. A computer program or a computer-readable media containing means for carrying out a method as defined in any of claims 1 to 14.