A novel non-bile acid FXR agonist EDP-305 potently suppresses liver injury and fibrosis without worsening of ductular reaction.

BACKGROUND: EDP-305 is a novel and potent farnesoid X receptor (FXR) agonist, with no/minimal cross-reactivity to TGR5 or other nuclear receptors. Herein we report therapeutic efficacy of EDP-305, in direct comparison with the first-in-class FXR agonist obeticholic acid (OCA), in mouse models of liver disease. METHODS: EDP-305 (10 and 30 mg/kg/day) or OCA (30mg/kg/day) was tested in mouse models of pre-established biliary fibrosis (BALBc.Mdr2-/-, n = 9-12/group) and steatohepatitis induced by methionine/choline-deficient diet (MCD, n = 7-12/group). Effects on biliary epithelium were evaluated in vivo and in primary EpCAM + hepatic progenitor cell (HPC) cultures. RESULTS: In a BALBc.Mdr2-/- model, EDP-305 reduced serum transaminases by up to 53% and decreased portal pressure, compared to untreated controls. Periportal bridging fibrosis was suppressed by EDP-305 at both doses, with up to a 39% decrease in collagen deposition in high-dose EDP-305. In MCD-fed mice, EDP-305 treatment reduced serum ALT by 62% compared to controls, and profoundly inhibited perisinusoidal 'chicken wire' fibrosis, with over 80% reduction in collagen deposition. In both models, treatment with 30mg/kg OCA reduced serum transaminases up to 30%, but did not improve fibrosis. The limited impact on fibrosis was mediated by cholestasis-independent worsening of ductular reaction by OCA in both disease models; OCA but not EDP-305 at therapeutic doses promoted ductular proliferation in healthy mice and favoured differentiation of primary HPC towards cholangiocyte lineage in vitro. CONCLUSIONS: EDP-305 potently improved pre-established liver injury and hepatic fibrosis in murine biliary and metabolic models of liver disease, supporting the clinical evaluation of EDP-305 in fibrotic liver diseases including cholangiopathies and non-alcoholic steatohepatitis.

Choline and its metabolites are differently associated with cardiometabolic risk factors, history of cardiovascular disease, and MRI-documented cerebrovascular disease in older adults.

Background: There is a potential role of choline in cardiovascular and cerebrovascular disease through its involvement in lipid and one-carbon metabolism.Objective: We evaluated the associations of plasma choline and choline-related compounds with cardiometabolic risk factors, history of cardiovascular disease, and cerebrovascular pathology.Design: A cross-sectional subset of the Nutrition, Aging, and Memory in Elders cohort who had undergone MRI of the brain (n = 296; mean ± SD age: 73 ± 8.1 y) was assessed. Plasma concentrations of free choline, betaine, and phosphatidylcholine were measured with the use of liquid-chromatography-stable-isotope dilution-multiple-reaction monitoring-mass spectrometry. A volumetric analysis of MRI was used to determine the cerebrovascular pathology (white-matter hyperintensities and small- and large-vessel infarcts). Multiple linear and logistic regression models were used to examine relations of plasma measures with cardiometabolic risk factors, history of cardiovascular disease, and radiologic evidence of cerebrovascular pathology.Results: Higher concentrations of plasma choline were associated with an unfavorable cardiometabolic risk-factor profile [lower high-density lipoprotein (HDL) cholesterol, higher total homocysteine, and higher body mass index (BMI)] and greater odds of large-vessel cerebral vascular disease or history of cardiovascular disease but lower odds of small-vessel cerebral vascular disease. Conversely, higher concentrations of plasma betaine were associated with a favorable cardiometabolic risk-factor profile [lower low-density lipoprotein (LDL) cholesterol and triglycerides] and lower odds of diabetes. Higher concentrations of plasma phosphatidylcholine were associated with characteristics of both a favorable cardiometabolic risk-factor profile (higher HDL cholesterol, lower BMI, lower C-reactive protein, lower waist circumference, and lower odds of hypertension and diabetes) and an unfavorable profile (higher LDL cholesterol and triglycerides).Conclusion: Choline and its metabolites have differential associations with cardiometabolic risk factors and subtypes of vascular disease, thereby suggesting differing roles in the pathogenesis of cardiovascular and cerebral large-vessel disease compared with that of small-vessel disease.

Recommendations for the Generation, Quantification, Storage, and Handling of Peptides Used for Mass Spectrometry-Based Assays.

BACKGROUND: For many years, basic and clinical researchers have taken advantage of the analytical sensitivity and specificity afforded by mass spectrometry in the measurement of proteins. Clinical laboratories are now beginning to deploy these work flows as well. For assays that use proteolysis to generate peptides for protein quantification and characterization, synthetic stable isotope-labeled internal standard peptides are of central importance. No general recommendations are currently available surrounding the use of peptides in protein mass spectrometric assays. CONTENT: The Clinical Proteomic Tumor Analysis Consortium of the National Cancer Institute has collaborated with clinical laboratorians, peptide manufacturers, metrologists, representatives of the pharmaceutical industry, and other professionals to develop a consensus set of recommendations for peptide procurement, characterization, storage, and handling, as well as approaches to the interpretation of the data generated by mass spectrometric protein assays. Additionally, the importance of carefully characterized reference materials-in particular, peptide standards for the improved concordance of amino acid analysis methods across the industry-is highlighted. The alignment of practices around the use of peptides and the transparency of sample preparation protocols should allow for the harmonization of peptide and protein quantification in research and clinical care.

Rapid LC-MRM-MS assay for simultaneous quantification of choline, betaine, trimethylamine, trimethylamine N-oxide, and creatinine in human plasma and urine.

There is a growing interest in analyzing choline, betaine, and their gut microbial metabolites including trimethylamine (TMA) and trimethylamine N-oxide (TMAO) in body fluids due to the high relevance of these compounds for human health and diseases. A stable isotope dilution (SID)-LC-MRM-MS assay was developed for the simultaneous determination of choline, betaine, TMA, TMAO, and creatinine in human plasma and urine. The assay was validated using quality control (QC) plasma samples, spiked at low, medium, and high levels. Freeze-thaw stability was also evaluated. The utility of this assay for urine was demonstrated using a nutritional clinical study on the effect of various egg doses on TMAO production in humans. This assay has a wide dynamic range (R2 > 0.994) for all the analytes (choline: 0.122-250 µM; betaine: 0.488-1000 µM; TMA: 0.244-250 µM; TMAO: 0.061-62.5 µM; and creatinine: 0.977-2000 µM). High intra- and inter-day precision (CV < 6%) and high accuracy (< 15% error) were observed from the QC plasma samples. The assay is reliable for samples undergoing multiple freeze-thaw cycles (tested up to eight cycles). The assay also works for urine samples as demonstrated by a clinical study in which we observed a significant, positive linear response to various egg doses for urinary concentrations of all the analytes except creatinine. A rapid SID-LC-MRM-MS assay for simultaneous quantification of choline, betaine, TMA, TMAO, and creatinine has been developed and validated, and is expected to find wide application in nutrition and cardiovascular studies as well as diagnosis and management of trimethylaminuria.

Liver transplantation for treatment of severe S-adenosylhomocysteine hydrolase deficiency.

A child with severe S-adenosylhomocysteine hydrolase (AHCY) deficiency (AHCY c.428A>G, p.Tyr143Cys; c.982T>G, p.Tyr328Asp) presented at 8 months of age with growth failure, microcephaly, global developmental delay, myopathy, hepatopathy, and factor VII deficiency. Plasma methionine, S-adenosylmethionine (AdoMet), and S-adenosylhomocysteine (AdoHcy) were markedly elevated and the molar concentration ratio of AdoMet:AdoHcy, believed to regulate a myriad of methyltransferase reactions, was 15% of the control mean. Dietary therapy failed to normalize biochemical markers or alter the AdoMet to AdoHcy molar concentration ratio. At 40 months of age, the proband received a liver segment from a healthy, unrelated living donor. Mean AdoHcy decreased 96% and the AdoMet:AdoHcy concentration ratio improved from 0.52±0.19 to 1.48±0.79 mol:mol (control 4.10±2.11 mol:mol). Blood methionine and AdoMet were normal and stable during 6 months of follow-up on an unrestricted diet. Average calculated tissue methyltransferase activity increased from 43±26% to 60±22%, accompanied by signs of increased transmethylation in vivo. Factor VII activity increased from 12% to 100%. During 6 postoperative months, head growth accelerated 4-fold and the patient made promising gains in gross motor, language, and social skills.

Large-Scale Interlaboratory Study to Develop, Analytically Validate and Apply Highly Multiplexed, Quantitative Peptide Assays to Measure Cancer-Relevant Proteins in Plasma.

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens to hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility, and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here, we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and seven control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data, we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to subnanogram/ml sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and interlaboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy-isotope-labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an interlaboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality control measures, enables sensitive, specific, reproducible, and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.

Headspace SPME-GC-MS metabolomics analysis of urinary volatile organic compounds (VOCs).

In this chapter, we describe the procedure for metabolic profiling of hundreds of urinary volatile organic compounds (VOCs) using headspace solid-phase microextraction (SPME) coupled to gas chromatography-mass spectrometry (GC-MS). SPME is a solvent-free technology that is reproducible, fast, cost effective, and versatile in extracting small molecular weight organic compounds (metabolites) from biofluids using a fiber that is coated with an extracting phase. After extraction, the SPME fiber can be directly injected to the GC-MS, where the extracted metabolites will desorb thermally from the fiber, elute along a GC column, and finally enter into the MS for detection. The analysis of urine samples is presented using this approach.

Effect of egg ingestion on trimethylamine-N-oxide production in humans: a randomized, controlled, dose-response study.

BACKGROUND: It is important to understand whether eating eggs, which are a major source of dietary choline, results in increased exposure to trimethylamine-N-oxide (TMAO), which is purported to be a risk factor for developing heart disease. OBJECTIVE: We determined whether humans eating eggs generate TMAO and, if so, whether there is an associated increase in a marker for inflammation [ie, high-sensitivity C-reactive protein (hsCRP)] or increased oxidation of low-density lipoprotein (LDL). DESIGN: In a longitudinal, double-blind, randomized dietary intervention, 6 volunteers were fed breakfast doses of 0, 1, 2, 4, or 6 egg yolks. Diets were otherwise controlled on the day before and day of each egg dose with a standardized low-choline menu. Plasma TMAO at timed intervals (immediately before and 1, 2, 4, 8, and 24 h after each dose), 24-h urine TMAO, predose and 24-h postdose serum hsCRP, and plasma oxidized LDL were measured. Volunteers received all 5 doses with each dose separated by >2-wk washout periods. RESULTS: The consumption of eggs was associated with increased plasma and urine TMAO concentrations (P < 0.01), with ∼14% of the total choline in eggs having been converted to TMAO. There was considerable variation between individuals in the TMAO response. There was no difference in hsCRP or oxidized LDL concentrations after egg doses. CONCLUSIONS: The consumption of ≥2 eggs results in an increased formation of TMAO. Choline is an essential nutrient that is required for normal human liver and muscle functions and important for normal fetal development. Additional study is needed to both confirm the association between TMAO and atherosclerosis and identify factors, microbiota and genetic, that influence the generation of TMAO before policy and medical recommendations are made that suggest reduced dietary choline intake.

Metabolomics approaches for characterizing metabolic interactions between host and its commensal microbes.

It is increasingly evident that the gut microbiota is involved in the regulation of multiple mammalian metabolic pathways through a series of interactive host-microbiota metabolic, signaling, and immune-inflammatory axes that physiologically connect the gut, liver, brain, and other organs. Correlation of the metabotypes with the gut microbial profiles derived from culture-independent molecular techniques is increasingly useful for deciphering inherent and intimate host-microbe relationships. Real-time analysis of the small molecule metabolites derived from gut microbial-host co-metabolism is essential for understanding the metabolic functions of the gut microbiome and has tremendous implications for personalized healthcare strategies. Metabolomics, an array of analytical techniques that includes high resolution NMR spectroscopy and chromatography-MS in conjunction with chemometrics and bioinformatics tools, enables characterization of the metabolic footprints of mammalian hosts that correlate with the microbial community in the intestinal tract. The metabolomics approach provides important information of a complete spectrum of metabolites produced from the gut microbial-mammalian co-metabolism and is improving our understanding of the molecular mechanisms underlying multilevel host-microbe interactions. In this review, the interactions of gut microbiota with their host are discussed and some examples of NMR- or MS-based metabolomics applications for characterizing the metabolic footprints of gut microbial-host co-metabolism are described. Advances in the metabolomic analysis of bile acids, short-chain fatty acids, and choline metabolism are also summarized.

Design, implementation and multisite evaluation of a system suitability protocol for the quantitative assessment of instrument performance in liquid chromatography-multiple reaction monitoring-MS (LC-MRM-MS).

Multiple reaction monitoring (MRM) mass spectrometry coupled with stable isotope dilution (SID) and liquid chromatography (LC) is increasingly used in biological and clinical studies for precise and reproducible quantification of peptides and proteins in complex sample matrices. Robust LC-SID-MRM-MS-based assays that can be replicated across laboratories and ultimately in clinical laboratory settings require standardized protocols to demonstrate that the analysis platforms are performing adequately. We developed a system suitability protocol (SSP), which employs a predigested mixture of six proteins, to facilitate performance evaluation of LC-SID-MRM-MS instrument platforms, configured with nanoflow-LC systems interfaced to triple quadrupole mass spectrometers. The SSP was designed for use with low multiplex analyses as well as high multiplex approaches when software-driven scheduling of data acquisition is required. Performance was assessed by monitoring of a range of chromatographic and mass spectrometric metrics including peak width, chromatographic resolution, peak capacity, and the variability in peak area and analyte retention time (RT) stability. The SSP, which was evaluated in 11 laboratories on a total of 15 different instruments, enabled early diagnoses of LC and MS anomalies that indicated suboptimal LC-MRM-MS performance. The observed range in variation of each of the metrics scrutinized serves to define the criteria for optimized LC-SID-MRM-MS platforms for routine use, with pass/fail criteria for system suitability performance measures defined as peak area coefficient of variation <0.15, peak width coefficient of variation <0.15, standard deviation of RT <0.15 min (9 s), and the RT drift <0.5min (30 s). The deleterious effect of a marginally performing LC-SID-MRM-MS system on the limit of quantification (LOQ) in targeted quantitative assays illustrates the use and need for a SSP to establish robust and reliable system performance. Use of a SSP helps to ensure that analyte quantification measurements can be replicated with good precision within and across multiple laboratories and should facilitate more widespread use of MRM-MS technology by the basic biomedical and clinical laboratory research communities.

Alteration of bile acid metabolism in the rat induced by chronic ethanol consumption.

Our understanding of the bile acid metabolism is limited by the fact that previous analyses have primarily focused on a selected few circulating bile acids; the bile acid profiles of the liver and gastrointestinal tract pools are rarely investigated. Here, we determined how chronic ethanol consumption altered the bile acids in multiple body compartments (liver, gastrointestinal tract, and serum) of rats. Rats were fed a modified Lieber-DeCarli liquid diet with 38% of calories as ethanol (the amount equivalent of 4-5 drinks in humans). While conjugated bile acids predominated in the liver (98.3%), duodenum (97.8%), and ileum (89.7%), unconjugated bile acids comprised the largest proportion of measured bile acids in serum (81.2%), the cecum (97.7%), and the rectum (97.5%). In particular, taurine-conjugated bile acids were significantly decreased in the liver and gastrointestinal tract of ethanol-treated rats, while unconjugated and glycine-conjugated species increased. Ethanol consumption caused increased expression of genes involved in bile acid biosynthesis, efflux transport, and reduced expression of genes regulating bile acid influx transport in the liver. These results provide an improved understanding of the systemic modulations of bile acid metabolism in mammals through the gut-liver axis.

Metabolic Profiling of Green Tea Treatments in Zucker Diabetic Rats Using 1H NMR.

This study has investigated the metabolic effects of catechin-rich green tea (GT) and its formulation with ascorbic acid (AA) on the Zucker rat model of type 2 diabetes. AA is used to protect the GT catechins during digestion and increase bioavailability. Thirty two Zucker diabetic fatty (ZDF) rats were randomly divided into four groups (n=8 in each group) and treated with water, GT, AA and GT+AA respectively for five weeks. Urinary metabolic profiles were determined using 1H NMR spectroscopy. Fourteen metabolites were identified and their 24-hr excretions were quantified. Changes in the 14 metabolites demonstrated differential treatment effects on the metabolism of ZDF rats. GT and AA were found to be able to independently reduce urinary excretions of most metabolites that were over-excreted in the control diabetic rats, such as oxidative stress marker metabolites and TCA cycle metabolites. GT showed a great potential in controlling metabolic acidosis by suppressing the excretion of lactic acid and acetic acid from diabetic rats and GT+AA showed a remarkably stronger suppression than GT while AA was unable to suppress these two acids. Further investigation is needed to better understand the role of GT and/or formulated GT in altering the metabolic pathways in the diabetic animal model as well as in humans.

"Add to subtract": a simple method to remove complex background signals from the 1H nuclear magnetic resonance spectra of mixtures.

Because of its highly reproducible and quantitative nature and minimal requirements for sample preparation or separation, (1)H nuclear magnetic resonance (NMR) spectroscopy is widely used for profiling small-molecule metabolites in biofluids. However (1)H NMR spectra contain many overlapped peaks. In particular, blood serum/plasma and diabetic urine samples contain high concentrations of glucose, which produce strong peaks between 3.2 ppm and 4.0 ppm. Signals from most metabolites in this region are overwhelmed by the glucose background signals and become invisible. We propose a simple "Add to Subtract" background subtraction method and show that it can reduce the glucose signals by 98% to allow retrieval of the hidden information. This procedure includes adding a small drop of concentrated glucose solution to the sample in the NMR tube, mixing, waiting for an equilibration time, and acquisition of a second spectrum. The glucose-free spectra are then generated by spectral subtraction using Bruker Topspin software. Subsequent multivariate statistical analysis can then be used to identify biomarker candidate signals for distinguishing different types of biological samples. The principle of this approach is generally applicable for all quantitative spectral data and should find utility in a variety of NMR-based mixture analyses as well as in metabolite profiling.

Identification and quantification of metabolites in (1)H NMR spectra by Bayesian model selection.

MOTIVATION: Nuclear magnetic resonance (NMR) spectroscopy is widely used for high-throughput characterization of metabolites in complex biological mixtures. However, accurate interpretation of the spectra in terms of identities and abundances of metabolites can be challenging, in particular in crowded regions with heavy peak overlap. Although a number of computational approaches for this task have recently been proposed, they are not entirely satisfactory in either accuracy or extent of automation. RESULTS: We introduce a probabilistic approach Bayesian Quantification (BQuant), for fully automated database-based identification and quantification of metabolites in local regions of (1)H NMR spectra. The approach represents the spectra as mixtures of reference profiles from a database, and infers the identities and the abundances of metabolites by Bayesian model selection. We show using a simulated dataset, a spike-in experiment and a metabolomic investigation of plasma samples that BQuant outperforms the available automated alternatives in accuracy for both identification and quantification. AVAILABILITY: The R package BQuant is available at: http://www.stat.purdue.edu/~ovitek/BQuant-Web/.

Effect of collision energy optimization on the measurement of peptides by selected reaction monitoring (SRM) mass spectrometry.

Proteomics experiments based on Selected Reaction Monitoring (SRM, also referred to as Multiple Reaction Monitoring or MRM) are being used to target large numbers of protein candidates in complex mixtures. At present, instrument parameters are often optimized for each peptide, a time and resource intensive process. Large SRM experiments are greatly facilitated by having the ability to predict MS instrument parameters that work well with the broad diversity of peptides they target. For this reason, we investigated the impact of using simple linear equations to predict the collision energy (CE) on peptide signal intensity and compared it with the empirical optimization of the CE for each peptide and transition individually. Using optimized linear equations, the difference between predicted and empirically derived CE values was found to be an average gain of only 7.8% of total peak area. We also found that existing commonly used linear equations fall short of their potential, and should be recalculated for each charge state and when introducing new instrument platforms. We provide a fully automated pipeline for calculating these equations and individually optimizing CE of each transition on SRM instruments from Agilent, Applied Biosystems, Thermo-Scientific and Waters in the open source Skyline software tool ( http://proteome.gs.washington.edu/software/skyline ).

Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes.

Insulin is as a major postprandial hormone with profound effects on carbohydrate, fat, and protein metabolism. In the absence of exogenous insulin, patients with type 1 diabetes exhibit a variety of metabolic abnormalities including hyperglycemia, glycosurea, accelerated ketogenesis, and muscle wasting due to increased proteolysis. We analyzed plasma from type 1 diabetic (T1D) humans during insulin treatment (I+) and acute insulin deprivation (I-) and non-diabetic participants (ND) by (1)H nuclear magnetic resonance spectroscopy and liquid chromatography-tandem mass spectrometry. The aim was to determine if this combination of analytical methods could provide information on metabolic pathways known to be altered by insulin deficiency. Multivariate statistics differentiated proton spectra from I- and I+ based on several derived plasma metabolites that were elevated during insulin deprivation (lactate, acetate, allantoin, ketones). Mass spectrometry revealed significant perturbations in levels of plasma amino acids and amino acid metabolites during insulin deprivation. Further analysis of metabolite levels measured by the two analytical techniques indicates several known metabolic pathways that are perturbed in T1D (I-) (protein synthesis and breakdown, gluconeogenesis, ketogenesis, amino acid oxidation, mitochondrial bioenergetics, and oxidative stress). This work demonstrates the promise of combining multiple analytical methods with advanced statistical methods in quantitative metabolomics research, which we have applied to the clinical situation of acute insulin deprivation in T1D to reflect the numerous metabolic pathways known to be affected by insulin deficiency.

Advances in NMR-based biofluid analysis and metabolite profiling.

Significant improvements in NMR technology and methods have propelled NMR studies to play an important role in a rapidly expanding number of applications involving the profiling of metabolites in biofluids. This review discusses recent technical advances in NMR spectroscopy based metabolite profiling methods, data processing and analysis over the last three years.

13C-formylation for improved nuclear magnetic resonance profiling of amino metabolites in biofluids.

An increased interest in metabolite profiling is driving the need for improved analytical techniques with greater performance for a variety of important applications. Despite their limited sensitivity, nuclear magnetic resonance (NMR) methods are attractive because of their simplicity, reproducibility, quantitative nature, and wide applicability. The use of chemoselective isotopic tags has the potential to advance the application of NMR for analyzing metabolites in complex biofluids by allowing detection of metabolites down to the low micromoalr level with high resolution and specificity. Here, we report a new (13)C-tagging method using (13)C-formic acid that delivers high sensitivity, good quantitation, and excellent resolution for (1)H-(13)C 2D NMR profiling of amino metabolites. High reproducibility (coefficient of variation (CV) = 2%) was observed for metabolites in urine with concentrations down to 10 microM. As amino compounds comprise an important class of metabolites and small molecules of biological roles, this new method therefore should be amenable to a variety of applications.

Interdependence of signal processing and analysis of urine 1H NMR spectra for metabolic profiling.

Metabolic profiling of urine presents challenges because of the extensive random variation of metabolite concentrations and the dilution resulting from changes in the overall urine volume. Thus statistical analysis methods play a particularly important role; however, appropriate choices of these methods are not straightforward. Here we investigate constant and variance-stabilization normalization of raw and peak picked spectra, for use with exploratory analysis (principal component analysis) and confirmatory analysis (ordinary and Empirical Bayes t-test) in (1)H NMR-based metabolic profiling of urine. We compare the performance of these methods using urine samples spiked with known metabolites according to a Latin square design. We find that analysis of peak picked and logarithm-transformed spectra is preferred, and that signal processing and statistical analysis steps are interdependent. While variance-stabilizing transformation is preferred in conjunction with principal component analysis, constant normalization is more appropriate for use with a t-test. Empirical Bayes t-test provides more reliable conclusions when the number of samples in each group is relatively small. Performance of these methods is illustrated using a clinical metabolomics experiment on patients with type 1 diabetes to evaluate the effect of insulin deprivation.

R: A quantitative measure of NMR signal receiving efficiency.

Recognizing that the sensitivity of NMR is influenced by factors such as conductance and dielectric constant of the sample, we propose the receiving efficiency R to characterize how efficiently the NMR signal can be observed from a unit transverse magnetization in a sample under optimal probe tuning and matching conditions. Conveniently, the relative receiving efficiency can be defined as the ratio of the NMR signal induced by a unit transverse magnetization in a sample of interest and a reference solution. Based on the reciprocal relationship between excitation and observation in NMR, the relative receiving efficiency can be correlated with the 90 degrees pulse length (tau(90)). In the special case of perfect probe tuning (impedance matched to 50 Omega), R is inversely proportional to tau(90). Application of the NMR receiving efficiency in quantitative analysis potentially enables a single external concentration reference for almost any sample, eliminating the need to know its exact chemical composition or detailed electromagnetic properties.