Hartmut Schäfer

Evidence of different metabolic phenotypes in humans

The study of metabolic responses to drugs, environmental changes, and diseases is a new promising area of metabonomic research. Metabolic fingerprints can be obtained by analytical techniques such as nuclear magnetic resonance (NMR). In principle, alterations of these fingerprints due to appearance/disappearance or concentration changes of metabolites can provide early evidences of, for example, onset of diseases. A major drawback in this approach is the strong day-to-day variability of the individual metabolic fingerprint, which should be rather called a metabolic “snapshot.” We show here that a thorough statistical analysis performed on NMR spectra of human urine samples reveals an invariant part characteristic of each person, which can be extracted from the analysis of multiple samples of each single subject. This finding (i) provides evidence that individual metabolic phenotypes may exist and (ii) opens new perspectives to metabonomic studies, based on the possibility of eliminating the daily “noise” by multiple sample collection.

Precision High-Throughput Proton NMR Spectroscopy of Human Urine, Serum, and Plasma for Large-Scale Metabolic Phenotyping

Proton nuclear magnetic resonance (NMR)-based metabolic phenotyping of urine and blood plasma/serum samples provides important prognostic and diagnostic information and permits monitoring of disease progression in an objective manner. Much effort has been made in recent years to develop NMR instrumentation and technology to allow the acquisition of data in an effective, reproducible, and high-throughput approach that allows the study of general population samples from epidemiological collections for biomarkers of disease risk. The challenge remains to develop highly reproducible methods and standardized protocols that minimize technical or experimental bias, allowing realistic interlaboratory comparisons of subtle biomarker information. Here we present a detailed set of updated protocols that carefully consider major experimental conditions, including sample preparation, spectrometer parameters, NMR pulse sequences, throughput, reproducibility, quality control, and resolution. These results provide an experimental platform that facilitates NMR spectroscopy usage across different large cohorts of biofluid samples, enabling integration of global metabolic profiling that is a prerequisite for personalized healthcare.

Individual human phenotypes in metabolic space and time.

Differences between individual phenotypes are due both to differences in genotype and to exposure to different environmental factors. A fundamental contribution to the definition of the individual phenotype for clinical and therapeutic applications would come from a deeper understanding of the metabolic phenotype. The existence of unique individual metabolic phenotypes has been hypothesized, but the experimental evidence has been only recently collected. Analysis of individual phenotypes over the timescale of years shows that the metabolic phenotypes are largely invariant. The present work also supports the idea that the individual metabolic phenotype can also be considered a metagenomic entity that is strongly affected by both gut microbiome and host metabolic phenotype, the latter defined by both genetic and environmental contributions.

Targeted and Nontargeted Wine Analysis by 1H NMR Spectroscopy Combined with Multivariate Statistical Analysis. Differentiation of Important Parameters: Grape Variety, Geographical Origin, Year of Vintage

The authenticity, the grape variety, the geographical origin, and the year of vintage of wines produced in Germany were investigated by (1)H NMR spectroscopy in combination with several steps of multivariate data analysis including principal component analysis (PCA), linear discrimination analysis (LDA), and multivariate analysis of variance (MANOVA) together with cross-validation (CV) embedded in a Monte Carlo resampling approach (MC) and others. A total of about 600 wines were selected and carefully collected from five wine-growing areas in the southern and southwestern parts of Germany. Simultaneous saturation of the resonances of water and ethanol by application of a low-power eight-frequency band irradiation using shaped pulses allowed for high receiver gain settings and hence optimized signal-to-noise ratios. Correct prediction of classification of the grape varieties of Pinot noir, Lemberger, Pinot blanc/Pinot gris, Müller-Thurgau, Riesling, and Gewürztraminer of 95% in the wine panel was achieved. The classification of the vintage of all analyzed wines resulted in correct predictions of 97 and 96%, respectively, for vintage 2008 (n = 318) and 2009 (n = 265). The geographic origin of all wines from the largest German wine-producing regions, Rheinpfalz, Rheinhessen, Mosel, Baden, and Württemberg, could be predicted 89% correctly on average. Each NMR spectrum could be regarded as the individual fingerprint of a wine sample, which includes information about variety, origin, vintage, physiological state, technological treatment, and others.

Mixture analysis by NMR as applied to fruit juice quality control

Nuclear magnetic resonance (NMR) spectroscopy is rapidly gaining importance in mixture analysis, originally driven by the pharmaceutical and nowadays also by clinical applications within metabonomics. Quality control of food‐related material has very similar requirements, as it also deals with mixtures, and many of the compounds found in body fluids are analyzed as well. NMR allows analysis in two ways within one experiment: namely, targeted and untargeted. Targeted stands for the safe identification and consequent quantification of individual compounds, whereas untargeted means the detection of all deviations visible by NMR using statistical analysis based on normality models. Very important is the stability and reproducibility of the NMR instrumentation used, and this means inherent minimized system internal variance. NMR is especially suited for such requirements, as it allows detection of the smallest concentration changes of many metabolites simultaneously. High‐throughput flow‐injection NMR as the basis for fruit juice screening allows low cost per sample and delivers substantially more relevant information than any other method and is probably the only method to produce such results. Copyright

Application of automated eightfold suppression of water and ethanol signals in 1H NMR to provide sensitivity for analyzing alcoholic beverages

The 400u2009MHz 1H NMR analysis of alcoholic beverages using standard pulse programs lacks the necessary sensitivity to detect minor constituents such as methanol, acetaldehyde or ethyl acetate. This study investigates the application of a shaped pulse sequence during the relaxation delay to suppress the eight 1H NMR frequencies of water and ethanol (the OH singlet of both water and ethanol, as well as the CH2 quartet and CH3 triplet of ethanol). The sequence of reference measurement for frequency determination followed by the suppression experiment is controlled by a macro in the acquisition software so that a measurement under full automation is possible (12u2009min per sample total time). Additionally, sample preparation was optimized to avoid precipitation, which is facilitated by 1u2009:u20091 dilution with ethanol and pH 7.4 buffer.

Synergistic effect of the simultaneous chemometric analysis of 1H NMR spectroscopic and stable isotope (SNIF-NMR, 18O, 13C) data: Application to wine analysis

It is known that (1)H NMR spectroscopy represents a good tool for predicting the grape variety, the geographical origin, and the year of vintage of wine. In the present study we have shown that classification models can be improved when (1)H NMR profiles are fused with stable isotope (SNIF-NMR, (18)O, (13)C) data. Variable selection based on clustering of latent variables was performed on (1)H NMR data. Afterwards, the combined data of 718 wine samples from Germany were analyzed using linear discriminant analysis (LDA), partial least squares-discriminant analysis (PLS-DA), factorial discriminant analysis (FDA) and independent components analysis (ICA). Moreover, several specialized multiblock methods (common components and specific weights analysis (ComDim), consensus PCA and consensus PLS-DA) were applied to the data. The best improvement in comparison with (1)H NMR data was obtained for prediction of the geographical origin (up to 100% for the fused data, whereas stable isotope data resulted only in 60-70% correct prediction and (1)H NMR data alone in 82-89% respectively). Certain enhancement was obtained also for the year of vintage (from 88 to 97% for (1)H NMR to 99% for the fused data), whereas in case of grape varieties improved models were not obtained. The combination of (1)H NMR data with stable isotope data improves efficiency of classification models for geographical origin and vintage of wine and can be potentially used for other food products as well.

NMR-Based Multi Parametric Quality Control of Fruit Juices: SGF Profiling

With SGF Profiling™ we introduce an NMR-based screening method for the quality control of fruit juices. This method has been developed in a joint effort by Bruker BioSpin GmbH and SGF International e.V. The system is fully automated with respect to sample transfer, measurement, data analysis and reporting and is set up on an Avance 400 MHz flow-injection NMR spectrometer. For each fruit juice a multitude of parameters related to quality and authenticity are evaluated simultaneously from a single data set acquired within a few minutes. This multimarker/multi-aspect NMR screening approach features low cost-per-sample and is highly competitive with conventional and targeted fruit juice quality control methods.

Validation studies for multicomponent quantitative NMR analysis: the example of apple fruit juice

Laboratories intending to work as official laboratories for food control have to be accredited according to ISO/IEC 17025. This necessitates the use of validated analytical methods. In this study, we present validation results of the recently commercialized “JuiceScreener” based on nuclear magnetic resonance (NMR) spectroscopy with apple juice as application example. The quantitative analysis included 29 compounds such as major sugars, amino acids, organic acids, as well as acetoin, arbutin, benzaldehyde, hydroxymethylfurfural, acetaldehyde, methanol, and ethanol. Limit of detection (LOD), limit of quantification (LOQ), coefficients of variation (CV) for replicated measurements, repeatability, linear range, and recoveries were determined. The LOD and LOQ values varied in the 0.48–16xa0mg/L and in the 1.9–122xa0mg/L ranges with the lowest values for shikimic acid and highest for the principal sugars. The 1H NMR assays were linear in broad concentration ranges (Rxa0>xa00.99), encompassed typical concentration in apple juices, and are sufficient to control the requirements of the code of practice of the European fruit juice association. Recoveries between 92 and 109xa0% on average for five separate standard additions were obtained. The average CVs were found to be 3.0xa0% (intraday) and 3.6xa0% (interday) excluding sample preparation (by measuring five time one solution) and 5.5xa0% (intraday) and 6.2xa0% (interday) including sample preparation (by preparing and analyzing five separate samples). The NMR method was judged as suitable for the simultaneous quantification of compounds in apple juice for official food control purposes. Our results show that multiparameter NMR methods can be successfully validated with standard instrumentarium and that they are fit for the purpose of official food control.

NMR-Based Screening for Inborn Errors of Metabolism: Initial Results from a Study on Turkish Neonates

Approximately 1 in 400 neonates in Turkey is affected by inherited metabolic diseases. This high prevalence is at least in part due to consanguineous marriages. Standard screening in Turkey now covers only three metabolic diseases (phenylketonuria, congenital hypothyroidism, and biotinidase deficiency). Once symptoms have developed, tandem-MS can be used, although this currently covers only up to 40 metabolites. NMR potentially offers a rapid and versatile alternative.We conducted a multi-center clinical study in 14 clinical centers in Turkey. Urine samples from 989 neonates were collected and investigated by using NMR spectroscopy in two different laboratories. The primary objective of the present study was to explore the range of variation of concentration and chemical shifts of specific metabolites without clinically relevant findings that can be detected in the urine of Turkish neonates. The secondary objective was the integration of the results from a healthy reference population of neonates into an NMR database, for routine and completely automatic screening of congenital metabolic diseases.Both targeted and untargeted analyses were performed on the data. Targeted analysis was aimed at 65 metabolites. Limits of detection and quantitation were determined by generating urine spectra, in which known concentrations of the analytes were added electronically as well as by real spiking. Untargeted analysis involved analysis of the whole spectrum for abnormal features, using statistical procedures, including principal component analysis. Outliers were eliminated by model building. Untargeted analysis was used to detect known and unknown compounds and jaundice, proteinuria, and acidemia. The results will be used to establish a database to detect pathological concentration ranges and for routine screening.