NMR (nuclear magnetic resonance) spectroscopy is an analytical measurement method which makes it possible to make statements at the molecular level about the concentration, the composition and structure of simple or complex molecules and mixtures, without altering the sample itself. This can be done in liquids, but also in solids. The principle is based on the interaction of individual nuclear spins – in the simplest case, protons or hydrogen (1H) – with a strong static magnetic field applied from the outside, in which the spins align along the magnetic field (in the z-direction) (Figure 1).
By means of suitable radio frequency pulses perpendicular to the static magnetic field, the spins, which are in resonance with the incident pulse, can be selectively excited and thus tilted by a defined angle. This leads to a precession of the spins, which is comparable to that of a gyroscope that is disturbed in its movement by a quick push. The frequency of this precession on the x-y-plane is the actual quantity to be measured and depends on the strength of the externally applied magnetic field. It is referred to as the Larmor frequency.
The excited nuclear spins can be detected until they relax back to their equilibrium state – parallel to the external magnetic field – again (longitudinal or T1 relaxation). The detected signal actually decreases even faster, since different nuclear spins precess at different resonance frequencies. Over time they lose coherence, so that the spins point in different directions and the sum of their signals cancels each other out (transverse or T2 relaxation).
The resonance frequency of a specific nuclear spin is affected by its chemical environment: if, e.g., a proton is in close proximity to an aromatic ring or a carboxylic acid group, it is less shielded from the magnetic field than another proton that is only bound to an aliphatic radical. This leads to so-called chemical shifts that describe the frequency of the signal relative to a fixed standard [1, 2].
In addition to hydrogen, which occurs ubiquitously in all organic molecules, one may, inter alia, also measure 13C, 15N or 31P and thus obtain additional important information on other nuclei. It is also possible to include multidimensional NMR spectra that either measure homonuclear couplings between two identical types of nuclei (usually only 1H) or heteronuclear couplings between different types of nuclei (e.g., 1H and 13C or 1H and 15N). This allows conclusions about bonding patterns and spin systems, but it is also possible to determine distances between two nuclei each by means of the NOE (Nuclear Overhauser Effect) and so decipher complete structures of proteins or other macromolecules [1–3].
The fine structure of individual signals in the spectrum provides information on the directly adjacent nuclei with which the observed nucleus “couples”. These so-called J-couplings cause signals to appear not only as a simple Lorentzian-shaped signal (singlet), but as doublets, triplets, quartets, or multiplets. These splitting patterns lead to more complex spectra with additional information, but also complicate their interpretation. With the help of a suitable 2D Jres (J-resolved) pulse program, these couplings can be transferred to a second dimension, thus obtaining a highly simplified spectrum in the first dimension and a detailed description of the coupling patterns in the second dimension [3, 4].
Relaxation measurements are used to determine the time it takes for a nucleus to return to the equilibrium state after excitation. Both, the T1 and T2 relaxation times can vary for complete molecules, but also between individual nuclei in one molecule. External effects such as viscosity or temperature play a crucial role. However, relaxation times tend to be longer for smaller molecules, which is due to their higher mobility and lower energy exchange with their environment. This circumstance can be utilized in order to filter for specific relaxation times via so-called relaxation-edited pulse programs in a targeted manner during measurement [3, 5].
A similar process is also possible by using diffusion-edited pulse programs. Diffusion measurements are aimed at filtering different substances not – as described earlier – by their relaxation times, but according to their diffusion behavior. Diffusion is closely related to the mobility and the size of the corresponding molecule or macromolecule. The faster a molecule moves, the more signal loss is obtained in diffusion-weighted spectra. If one measures a plurality of differently weighted diffusion spectra one after another, it is even possible to determine the absolute diffusion coefficient of a molecule in the solution and thus to draw conclusions about its size or radius. Again, specially edited pulse programs can be used to filter out only the slowly diffusing particles, or to emphasize highly mobile molecules via the difference from the original spectrum [6–8].
So far, NMR spectroscopy has been reserved for experts who know how to use the complex equipment, which made a routine diagnostic use largely impossible. Current products from commercial vendors have largely cleared this hurdle, however, through comprehensive automation and standardization, both in terms of the sample preparation and in the actual measurement. Devices commonly used in research can also meet the technical requirements, but frequently are defeated by their own limitations in terms of process control and software standardization. The advantage of commercial systems can also be seen in terms of sample throughput: it is now possible to measure several hundred samples per device and day. As an emerging technology, NMR spectroscopy thus offers flexible and sophisticated analytical capabilities that could soon find their way into clinical laboratories.
NMR analysis of human serum
Since, in principle, any organic substance contains hydrogen atoms, 1H-NMR-spectroscopy is ideally suited for detecting a large number of different substances in a single measurement. A great advantage is that all the information is obtained in a single spectrum. This eliminates the inaccuracies from different pre-analytical steps, such as are required by many other methods. Therefore, NMR spectra allow for an excellent comparability within one measurement, so that even subtle changes of metabolites relative to each other are detectable. While the quantification of the components of a spectrum previously used to be time-consuming manual work for which NMR experts were needed, current software methods, with good standardization, allow for fully automatic recognition and quantification of many signals in the spectrum. Such systems will also be available shortly as commercial products.
In principle, any type of liquid sample is suitable for NMR analysis: urine, blood, cerebrospinal fluid, body fluid samples, etc. In practice, serum and urine play an especially important role. Generally, the NMR spectroscopic analysis of whole blood would also be possible. However, the additional information obtained via the signals from the cellular components and the coagulation factors is usually not desired. The material of choice is therefore serum, but plasma can also be analyzed as long as the NMR signals of the anticoagulants contained (e.g., heparin, EDTA, citrate, etc.) do not overlap the signals to be analyzed.
A typical NMR spectrum of human serum is shown in Figure 2. Some predominant signals can be seen between 6 and 0 ppm. In addition, above 6 ppm, but also spread out over the remaining frequency range, one can see broad unstructured background signals, which are caused mainly by proteins. The very narrow lines are due to small metabolites such as amino acids or sugars, which have a high mobility in the solution. The dominant broader signals arise from lipoproteins, the transport vehicles of lipids . In aqueous samples, the solvent signal is generally suppressed by a suitable pulse program, as it would otherwise dominate the entire spectrum. The signal at about 4.5 ppm shown in Figure 2 represents the residual water signal that was not completely suppressed during the measurement.
As a matter of principle, in NMR spectra not the entire molecules are observed but individual distinctive molecular groups, such as methyl (-CH3), methylene (-CH2-) or choline groups (-N(CH3)3), because an entire molecule consists of many individual signals. If the molecular structure is known, a quantitative statement can be made about the number of corresponding protons.
Analysis of metabolites
In addition to proteins and lipoproteins that are present as globular aggregates, serum mainly contains small molecules that can move more or less freely. While salts cannot be analyzed by 1H-NMR spectroscopy due to the lack of hydrogen, monomeric building blocks such as sugars or amino acids can be assigned quite clearly. They yield very narrow signals and therefore can be easily quantified.
By now, almost all the signals in the spectrum of a donor’s serum can be identified. Through various one- and two-dimensional, as well as relaxation or diffusion-edited pulse programs, both small metabolites as well as lipoprotein and protein signals have been identified [5, 9]. By suppressing small metabolites during the measurement, it was possible for the first time to generate spectra of lipoproteins that did not have to be isolated from the serum first. Rather, any number of spectra were created based on the different mobility of the molecules by way of a suitable combination of relaxation and diffusion-edited NMR spectroscopy . Furthermore, the diffusion coefficients of some metabolites were determined simultaneously in a single serum sample using two-dimensional homonuclear TOCSY (total correlated spectroscopy) .
NMR spectroscopy provides numerous resources for the targeted selection of the desired information and also for structure determination. However, if one wants to absolutely determine the actual concentration of a substance, it is best to fall back on 1H-NMR spectroscopy, which is not only much faster in comparison to other methods, but also produces quantitative results without further action or by way of simple corrective calculations .
For the quantitative analysis of small metabolites, it is advantageous to eliminate the background, which is caused by macromolecules. It has been shown that diffusion-edited pulse programs yielded NMR spectra of the high molecular weight components that were nearly identical to the regular 1H-spectra of ultra-filtered serum samples from the laboratory . By applying differencing methods to the NMR spectrum of the entire serum, it was possible only to represent and quantify efficiently the small molecules.
Differentiated analysis of lipoproteins
The analysis of lipoproteins (LP) is far from trivial, because a single particle is composed of hundreds of lipids and a few proteins, so-called apolipoproteins. These particles have an additional diversity to them, since each of the LP classes (CM, VLDL, LDL and HDL) is not homogeneous, but also exhibits differences in composition and size . Serum contains a complex distribution of heterogeneous LP classes, which are also overlapped by various serum proteins and metabolites. The composition of the LP and lipids in serum is reflected in the shape of the NMR spectra.
Due to the chemical shift of differently sized particles, a differential quantification of numerous LP-subclasses is possible. It has been shown that the ratio between the particle interior (in which the lipids are distributed unstructured) and the particle membrane (in which the lipids are radially arranged) manifests itself in a general directionality of the magnetization, i.e., parallel to the magnetic field or perpendicular to the magnetic field. For larger particles, this results in a lower shield, and consequently a higher chemical shift value than for smaller particles .
This size shift is sufficiently large to obtain a differentiation and was first used in the early 1990s for the quantification of LP in serum [14–17]. To this end, NMR-spectra of isolated LP (VLDL, LDL and HDL) were acquired and used as a basis for a fitting algorithm that was used to reconstruct the methyl region of serum spectra by way of the linear combination of the base spectra. Based on the intensity of the fitted base spectra, conclusions could be drawn about the LP distribution and, in addition, a high correlation (r>0.8) was identified with lipid concentrations determined the traditional way, which occurred in the respective LP to a particularly high degree. Thus, it was not only possible to quantify the LP, but also the lipids therein.
This approach was pushed ahead further by means of neural networks. Unlike the fitting methods, this variant provides a mathematically independent model that is not based on the spectra of isolated LP [18, 19]. For this purpose, serum spectra were recorded, and the associated lipid concentrations of the individual isolated LP were determined using enzymatic methods. In a training set, the methyl and methylene regions of the NMR spectra were set in relation to the corresponding lipid concentrations, and the fitted neural network was then tested in an unknown test set. The correlation with the biochemical data was very good (r=0.70–0.99), so that all LP main components were determined with high accuracy and in a very short time.
A comparison of these neural networks with multivariate analytical methods, in particular PLS models (partial least squares), confirmed the good correlation not only for different lipid concentrations (r=0.73–0.99), but also for the first time for the protein components of ApoAI (r=0.92) and ApoB (r=0.97) . Similarly good values were obtained from other statistical algorithms such as MCMC methods (Markov chain Monte Carlo) .
Furthermore, it is possible to detect the particle size based on the diffusion by NMR. This happens in so-called diffusion-weighted spectra (diffusion ordered spectroscopy, DOSY), in which ultimately the diffusion coefficients of LP can be determined. As well, direct conclusions about the particles’ radii are possible in this case; they were determined from isolated LP in a 2012 study . The correlation with particles, analyzed by electron microscopy, was very good (r=0.9).
A quantitative determination of the LP classes by their diffusion coefficients, which differ ever so slightly, is difficult and cannot be accomplished with a simple DOSY spectrum of serum due to the complex overlapping of the LP . However, when combined with multivariate chemometric decomposition methods, this method, too, can be used to quantify LP and various LP-subclasses .
The different analysis options require more or less effort and time. Ultimately, using simple 1H-spectroscopy, one can obtain a considerable wealth of information, in a matter of minutes, about the composition and concentration of the different metabolites, particularly in combination with mathematical evaluation methods. The results correlate very well with most conventional methods, but are less time consuming, can be automated and therefore have less room for error.
NMR in comparison to other methods
The current gold standard for LP analysis is ultracentrifugation (UC), which separates the LP according to their density. This can be done either in discrete steps or along a continuous density gradient [25, 26]. UC separation is time consuming and requires considerable manual work. Moreover, high salt concentrations are often used in this method, and the samples are exposed to strong external forces. Nevertheless, it is the only method by which one can isolate the individual LP components selectively from serum on a preparative scale. In addition, it is possible to obtain a further sub-fractionation of the LP (e.g., LDL or HDL) by way of density gradients [27, 28].
Size exclusion chromatography (SEC), which separates particles according to their size, was discussed as an alternative method, since it represents a much milder method, which also allows for work to be done in physiological buffers. Unfortunately, the separation efficiency of the total serum is not comparable to UC; the sample sizes are much smaller and there is also massive dilution of the samples [29, 30]. A sub-fractionation of individual LP fractions is possible in principle, but also requires prior isolation by means of UC and a subsequent concentration of the fractions [31, 32]. However, a further advantage of SEC is the direct-coupled analysis, e.g., through UV absorption. However, a quantitative measurement of individual lipid components is not possible in this way.
Electrophoresis separates the LP by size and charge. The samples can be stained either with a protein or lipid dye, and thus also be evaluated quantitatively . However, this method is not suitable for preparative purposes, since the sample sizes are extremely small. Furthermore, an additional purification step is necessary to isolate the LP from the gel matrix.
The classic analysis for lipid quantification is usually based on a cascade of enzymatic reactions and a subsequent quantitative determination of the absorption of a colored end product. Thus, cholesterol, cholesterol ester or triglycerides, e.g., are usually determined in a fully enzymatic manner – following hydrolysis, if necessary . This method is simple and inexpensive, but does require prior isolation of the sample material. Apart from this, this method does not produce much information about the composition of individual particles, or no information at all about the number or size of particles, because it is only the average concentration of the entire sample that is measured.
Increasingly, mass spectrometry has proven itself as an analytical method. Here, the mass of molecular fragments of the individual components is measured and quantified [34, 35]. In other words, one obtains information about the composition of the sample. Like the enzymatic method, this one, too, requires prior separation. The method is also expensive and requires expert knowledge.
NMR spectroscopy is the only analytical method to yield information on the size and composition of a serum sample, without having to fractionate it first. Furthermore, the sample can be measured in its physiological environment. A single, quick measurement provides information about the size distribution and composition of lipoproteins, the different protein components and small metabolites. It requires more material than the more common methods (at least 300 μL), but the sample remains largely unaltered and can thus often be re-used. In the past, this method, too, called for specialist know-how, and the equipment represented a significant investment. However current commercial products increasingly facilitate cost-efficient application of the method.
Table 1 gives an overview of the advantages and disadvantages of the methods shown.
Clinical application in studies
The distribution of LP classes and subclasses in the blood has long been the focus of research and is associated with many diseases. Since the curve shapes in NMR spectra change significantly with varying composition, an accurate analysis is promising.
Already at the end of the 1980s, a possible link between malignant tumors and the line width of methyl and methylene signals in 1H-NMR-spectra of serum was the subject of a controversial debate [36, 37]. As it turned out, the cause of the narrower lines was an increased TG and, thus also, VLDL level as well as a lower HDL concentration – as is found in healthy patients [38–40]. The application of multivariate fitting methods to NMR spectra allowed for more detailed information about the concentration levels of lipoproteins (VLDL, LDL and HDL) relative to each other .
The use of such fitting methods demonstrates the tremendous advantage of NMR compared to alternative analytical methods. By default, the concentration of lipids (cholesterol or TG) in serum or previously isolated LP is measured, but NMR provides information about the number and size of the respective particles without any prior separation. This trait was demonstrated for 3437 test subjects as part of the Framingham Offspring study in 2002 . It was shown, on a subset of subjects, that there was no direct connection between the concentration of LDL particles and the cholesterol contained therein, because the composition of lipids is subject to extreme variations in LDL. Traditional analytical methods would not be able to consider this fact, it was concluded. A high concentration of LDL cholesterol could mean one of the following: there are many particles with a low cholesterol content, or there are few particles with a high cholesterol content. Patients exhibiting the former would benefit from treatment for lowering LDL, but conventional analytical methods would not be able to detect that .
The different sizes of VLDL and LDL were also analyzed by NMR spectroscopy. A study of 918 children aged 10 to 17 years has shown that LDL particles are on average 0.1 nm smaller, and VLDL particles 0.7 nm larger, in boys than in girls. The VLDL size was also shown to be a positive function of the age of White (Caucasian) children, which was not true of other ethnicities . Black children generally had larger LDL and smaller VLDL, which was due to different lipid ratios. The corresponding HDL subclasses were examined in a subsequent study . Here, decreasing average particle sizes were measured with increasing age of boys and generally larger HDL particles in girls (compared to boys) and Black children (compared to White). However when the HDL subclasses were looked at, rather than the total HDL, these observations were reversed in some cases. The concentration of the larger HDL particles decreased with age, while the concentration of the smaller HDL particles remained more or less constant. In addition, correlations with the weight of the children, TG levels and LDL cholesterol were found. Further findings were obtained when comparing the body weight of the child with the TG levels and the various subclasses of VLDL . The average TG level tended to be higher in White children than in Black children. As well, the ratio of waist circumference to TG concentration and/or large VLDL was 2–6 times higher in White children than in Black children.
Changes in LP profiles are encountered particularly under extreme exertion or in stress situations. For example, a competition among 28 test subjects (triathletes) had a favorable effect on the distribution of the LP classes in their blood . NMR spectroscopy revealed a very significant reduction in small LDL particles, as well as a slight increase in large LDL and a minor decrease in small HDL particles.
A positive lifestyle generally has a positive effect on the LP distribution in the blood. In 2009, in a study 73 test subjects were told to follow a strict vegetarian, low-fat diet and to exercise regularly. This had a positive effect on their LDL levels, as was confirmed by NMR spectroscopy . However the mere change in diet to a low-cholesterol and low-fat diet at constant body weight produced a more favorable LP profile – in men this was even more pronounced than in post-menopausal women . Another study only looked at the influence of physical activity without a change in diet . To this end, the study participants were to exercise regularly – with varying intensity in three different groups – but they had to keep their body weight. The NMR analysis of LP showed that it was not the intensity that was instrumental in the improved laboratory values, but the amount of exercise.
Today, early detection and accurate risk assessment of cardiovascular disease is of particular medical interest. The link to the blood distribution of LP and/or the lipids contained therein is no longer disputed. The measurement of lipid concentrations, as is done in routine clinical practice, however, does not provide sufficient information about the number and size of the LP particles. Only the ApoB concentration should correlate with the particle concentration of LDL, but here too there is no information about their size. In addition, recent findings suggest that there are deviations from the known correlation of ApoB and the number of LDL particles . Therefore, several NMR studies were carried out to establish correlations for the LP profile in healthy and patients atrisk. For the severity of coronary heart disease (CHD), a positive correlation was found with large VLDL and small HDL particles, as well as a negative correlation with average-sized HDL particles, independent of the subject’s age . A subsequent study on older women discovered a connection between the clinical picture and particularly small LDL and an increased particle concentration , with the concentration being a better predictor both for CHD  and, in particular, for the metabolic syndrome . Differences in CHD in men and women were also examined, and the results confirmed what had already been known . Even though NMR spectroscopy, as a risk-prediction model, has not yet reached the level of established clinical diagnostics, it still has enormous potential. It may therefore come to be accepted as a good addition to the traditional spectrum of clinical diagnostics .
Recent studies on macrophages, which are involved in the formation of atherosclerosis following an excessive uptake of modified LDL, yielded interesting new findings in this area . For this purpose, patients’ monocytes were isolated and differentiated from macrophages. By adding ApoAI and HDL2, the efflux of cholesterol was initiated and analyzed quantitatively. At the same time, the LP profile of the patients was determined using NMR. A high concentration of small HDL and LDL and/or a low concentration of large LP (VLDL and CM) correlated with an increased efflux of cholesterol from macrophages. In contrast, no connection was found to the respective cholesterol levels. Subjects with a significant stenosis had a lower efflux of cholesterol.
Many other factors such as type 1 diabetes [58–60], enzyme activity  or hormone concentration  contribute significantly to the LP profile, and have been examined in numerous NMR studies.
The identification of the genetic loci responsible for the expression of the LP-subclass profile in CHD patients was first investigated in 2007 . The heritability of the subclass spectrum was determined by means of univariate and multivariate calculations, ranging for HDL and LDL from about 20% to 50%. In addition, the expression of the HDL concentration was localized on chromosome 18 (LOD 3.3) by linkage analysis, and that of the HDL particle size on the chromosome 12 (LOD 2.9 or 3.7 after multivariate adjustment). The respective concentrations and particle numbers were determined by NMR spectroscopy. More detailed phenotyping for HDL also resulted in interesting correlations for HDL size and metabolic enzymes such as LIPC (hepatic triglyceride lipase), PLTP (phospholipid transfer protein) or FBLN5 (fibulin-5) . With HDL sizes obtained by NMR spectroscopy, a better phenotyping was achieved than via HDL cholesterol levels. In an extended study of nearly 2000 samples, whose LP subclasses were analyzed in detail, eight genetic loci associated with LP subclasses were identified by cluster analysis and associations with known subfractions, and four loci that were traced back to serum lipids .
Metabolomics refers to the simultaneous detection of a large number of metabolites to obtain a metabolic “status report”. This approach is the logical continuation of omics-based research that, from genomics and transcriptomics as well as proteomics to metabolomics, moved ever closer to the (patho-)physiological aspects.
Unlike traditional biomarker approaches, this is usually not only about identifying individual molecules that may appear to be suitable diagnostic parameters. Instead, the underlying assumption of this approach is that different functional states of the organism are reflected in different metabolic patterns. Thus, factors like nutrition, activity and not least illnesses change the steady states of various metabolic pathways. To measure them and filter out relevant information from the data is the challenge that must be mastered in the development of metabolomics-based diagnostics .
As stated above, NMR spectroscopy is ideal for the reproducible detection of metabolic parameters, and thus represents an important technological pillar in this field. Accordingly, the method has already been used in various studies with different questions, of which we will highlight a few below.
In 2011, the effect of extensive fasting of up to 36 h was studied for a group of volunteers . NMR spectra of blood and urine, besides other analyses, yielded valuable information about fasting-related changes to the metabolites. Overall, this study identified a few new biomarkers, apart from the known markers like fatty acids, glycerol, and ketone bodies. These included α-aminobutyric acid and other amino and keto acids. Only recently, this approach was extended and studied again . Fifteen young and healthy males volunteered as subjects in a controlled program consisting of 36 h of fasting, a special liquid diet, sports, exposure to cold and numerous other tests (glucose tolerance test, lipid test, hair samples, blood, urine and breath tests). Using mass spectroscopy and NMR analyses, among 275 metabolites – particularly lipids and amino acids – it was possible to identify the metabolites that exhibited a high positive correlation over time as the best indicators of catabolic and anabolic conditions: e.g., the existing amount of chylomicrons and VLDL (r=0.9, NMR), and also those with a significant negative correlation such as carnitine and acylcarnitine (r=–0.66, MS).
The effect of special diets on the metabolic pattern was also examined in a study on weight loss . Three test groups of 31 women each were given ω-3- fish oil or a placebo over 24 weeks. In addition, two of the three groups completed a weight reduction program over 12 weeks. In subjects who were given fish oil rather than placebos, a specific change in the lipid profile was diagnosed regardless of the weight loss, which was explained by an increase of PL and a reduction of certain TG.
The NMR spectroscopic analysis of the LP profile combined with small metabolites was especially used also for improved risk assessment of diseases . As part of the Cardiovascular Risk in Young Finns study, 1595 test subjects aged between 24 and 39 years were tested. At the start and after 6 years, the intima-media thickness was determined and correlated with the corresponding blood levels. The best predictions were based on the concentration of LDL-cholesterol, HDL of average size and various metabolites such as tyrosine and glutamine – all determined by NMR.
Similar models were also discussed for the early detection of diabetes and its typical sequelae. In a study of 182 type-1 diabetic patients and 21 healthy subjects, a clear distinction was made between the two groups that was based solely on a different pattern in the 1H-NMR-spectra. Moreover, the prediction accuracy for nephropathy was examined and compared with biochemical values. The sensitivity of the NMR data at 87.1% (reference: 83.9%) was slightly better than the reference values; the specificity at 87.7% (reference: 95.9%) was slightly worse . A further study was based on 613 test subjects with type-1 diabetes who exhibited a wide range of complications, such as nephropathy, insulin resistance and metabolic syndrome. That study yielded promising results, too .
In a hypertension study, NMR spectroscopic serum analyses were used to investigate typical changes in groups of varying degrees of severity . Using chemometric methods in combination with 1H-NMR spectra, it was possible to separate 28 subjects with normal blood pressure effectively from those with slightly (19 subjects) or severely (17 subjects) elevated blood pressure.
Metabolomics on the basis of NMR spectroscopy has been successfully investigated especially in cancer research. A study of 36 liver cirrhosis patients and 39 patients suffering from hepatocellular cancer revealed a clearly elevated level of, e.g., acetate, N-acetyl glycoproteins, pyruvate and glutamine as well as a reduction in the levels of isoleucine, valine, or acetoacetate . In the case of oral cancer, it was possible not only to establish a differentiation of healthy from diseased patients, but also to differentiate the severity of the disease . Different levels of amino acids and sugars indicated a disturbed energy metabolism, i.e., lipolysis, Krebs cycle and amino acid degradation. In a study of 103 patients with colorectal adenocarcinoma – including 42 with locoregional carcinoma, 45 with liver metastases and 25 with extrahepatic metastases – a clear distinction was made between the different groups by means of NMR spectroscopy or gas chromatography . These results demonstrate the universal applicability of NMR in cancer research, leading to new insights into metabolic disorders. In the future, early detection of such diseases may be much more accurate and much faster by analyzing the special signal patterns in the blood.
NMR spectroscopy is rapidly becoming a new analytical option for the determination of small metabolites on the one hand and differentiated lipoprotein analysis on the other. In numerous, variously oriented studies, the method has already been used successfully. It requires only minimal sample preparation as well as little time and, as a result of advancing automation efforts, is becoming increasingly important as a routine application in clinical laboratories.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: None declared.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
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Original German online version at: http://www.degruyter.com/view/j/labm.2014.38.issue-3/labmed-2012-0075/labmed-2012-0075.xml?format=INT. The German article was translated by Compuscript Ltd. and authorized by the authors.