Metabolomics profiling of the free and total oxidised lipids in urine by LC-MS/MS: application in patients with rheumatoid arthritis.

Oxidised lipids, covering enzymatic and auto-oxidation-synthesised mediators, are important signalling metabolites in inflammation while also providing a readout for oxidative stress, both of which are prominent physiological processes in a plethora of diseases. Excretion of these metabolites via urine is enhanced through the phase-II conjugation with glucuronic acid, resulting in increased hydrophilicity of these lipid mediators. Here, we developed a bovine liver-ß-glucuronidase hydrolysing sample preparation method, using liquid chromatography coupled to tandem mass spectrometry to analyse the total urinary oxidised lipid profile including the prostaglandins, isoprostanes, dihydroxy-fatty acids, hydroxy-fatty acids and the nitro-fatty acids. Our method detected more than 70 oxidised lipids biosynthesised from two non-enzymatic and three enzymatic pathways in urine samples. The total oxidised lipid profiling method was developed and validated for human urine and was demonstrated for urine samples from patients with rheumatoid arthritis. Pro-inflammatory mediators PGF2α and PGF3α and oxidative stress markers iPF2α- IV, 11-HETE and 14-HDoHE were positively associated with improvement of disease activity score. Furthermore, the anti-inflammatory nitro-fatty acids were negatively associated with baseline disease activity. In conclusion, the developed methodology expands the current metabolic profiling of oxidised lipids in urine, and its application will enhance our understanding of the role these bioactive metabolites play in health and disease.

Delayed luminescence: an experimental protocol for Chinese herbal medicines.

In Chinese medicine, raw herbal materials are used in processed and unprocessed forms aiming to meet the different requirements of clinical practice. To assure the chemical quality and therapeutic properties of the herbs, fast and integrated systematic assays are required. So far, such assays have not been established. Delayed luminescence (DL) refers to a decaying long-term ultraweak photon emission after exposure to light. Its decay kinetics under certain conditions may be a sensitive indicator reflecting the internal structural and chemical/physiological state of a biological system. DL measurements have been used in many applications for quality control. However, relatively little research has been reported on dried plant material such as Chinese herbs. The objective of the present study is to establish a protocol for direct and rapid DL measurements of dried Chinese herbal materials, including the determination of the dependence on: (a) the optimal excitation time utilizing a white light source; (b) the optimal size of the grinded herbal particle; and (c) the humidity conditions before and during measurement. Results indicate that stable and reproducible curves of DL photon emission depend mainly on the water content of herbal materials. To investigate the application of the established DL measurement protocol, non-processed and processed Aconitum (Aconitum carmichaelii Debx.), wild and cultivated rhubarb (Rheum palmatum L.) and ginseng (Panax ginseng C.A.Mey) of different ages were measured using DL. The results suggest that DL technology is a potential tool for assessment of dried Chinese herb qualities. The results warrant a further exploration of this technique in relation to therapeutic properties of the herbs. Copyright © 2016 John Wiley & Sons, Ltd.

Differences between serum polar lipid profiles of male and female rheumatoid arthritis patients in response to glucocorticoid treatment.

OBJECTIVE: As there are pharmacological differences between males and females, and glucocorticoid (GC) treatment is associated with increased cardiovascular mortality rate in rheumatoid arthritis (RA) patients, it is important to study serum polar lipid profiles of male and female patients in response to GC therapy. Gender differences may require an adjustment to the treatment strategy for a selection of patients. METHODS: Serum samples from 281 RA patients were analysed using a targeted lipidomics platform. The differences in GC use and gender on polar lipid profiles were cross sectionally examined by multiple linear regressions, while correcting for confounding factors. RESULTS: Differences in polar lipids between GC users and non-GC users in females and males were merely restricted to lysophospholipids (lysophosphatidylcholines and lysophosphatidylethanolamines). Lysophospholipids in female patients treated with GCs were significantly higher than female patients not treated with GCs (p = 6.0 E-6), whereas no significant difference was observed in male GC users versus non-users (p = 0.397). CONCLUSION: The lysophospholipid profiles in response to GCs were significantly different between male and female RA patients, which may have implications for the cardiovascular risk of GC treatment.

Collagen Induced Arthritis in DBA/1J Mice Associates with Oxylipin Changes in Plasma.

Oxylipins play important roles in various biological processes and are considered as mediators of inflammation for a wide range of diseases such as rheumatoid arthritis (RA). The purpose of this research was to study differences in oxylipin levels between a widely used collagen induced arthritis (CIA) mice model and healthy control (Ctrl) mice. DBA/1J male mice (age: 6-7 weeks) were selected and randomly divided into two groups, namely, a CIA and a Ctrl group. The CIA mice were injected intraperitoneally (i.p.) with the joint cartilage component collagen type II (CII) and an adjuvant injection of lipopolysaccharide (LPS). Oxylipin metabolites were extracted from plasma for each individual sample using solid phase extraction (SPE) and were detected with high performance liquid chromatography/tandem mass spectrometry (HPLC-ESI-MS/MS), using dynamic multiple reaction monitoring (dMRM). Both univariate and multivariate statistical analyses were applied. The results in univariate Student's t-test revealed 10 significantly up- or downregulated oxylipins in CIA mice, which were supplemented by another 6 additional oxylipins, contributing to group clustering upon multivariate analysis. The dysregulation of these oxylipins revealed the presence of ROS-generated oxylipins and an increase of inflammation in CIA mice. The results also suggested that the collagen induced arthritis might associate with dysregulation of apoptosis, possibly inhibited by activated NF-κB because of insufficient PPAR-γ ligands.

Looking back into the future: 30 years of metabolomics at TNO.

Metabolites have played an essential role in our understanding of life, health, and disease for thousands of years. This domain became much more important after the concept of metabolism was discovered. In the 1950s, mass spectrometry was coupled to chromatography and made the technique more application-oriented and allowed the development of new profiling technologies. Since 1980, TNO has performed system-based metabolic profiling of body fluids, and combined with pattern recognition has led to many discoveries and contributed to the field known as metabolomics and systems biology. This review describes the development of related concepts and applications at TNO in the biomedical, pharmaceutical, nutritional, and microbiological fields, and provides an outlook for the future.

Developing computational model-based diagnostics to analyse clinical chemistry data.

This article provides methodological and technical considerations to researchers starting to develop computational model-based diagnostics using clinical chemistry data. These models are of increasing importance, since novel metabolomics and proteomics measuring technologies are able to produce large amounts of data that are difficult to interpret at first sight, but have high diagnostic potential. Computational models aid interpretation and make the data accessible for clinical diagnosis. We discuss the issues that a modeller has to take into account during the design, construction and evaluation phases of model development. We use the example of Particle Profiler development, a model-based diagnostic tool for lipoprotein disorders, as a case study, to illustrate our considerations. The case study also offers techniques for efficient model formulation, model calculation, workflow structuring and quality control.

Feasibility of electroextraction as versatile sample preconcentration for fast and sensitive analysis of urine metabolites, demonstrated on acylcarnitines.

In this work, we demonstrate the applicability of electroextraction (EE) to urine metabolites. To investigate which urine metabolite classes are susceptible to EE, off-line EE experiments were carried out with a prototype device, in which urine metabolites were electroextracted from ethyl acetate into water. The obtained extracts were examined with direct infusion MS and the results demonstrated that several compound classes could be extracted, amongst which amino acids and acylcarnitines. Acylcarnitines were selected for evaluation of the performance of EE. For this, the EE setup was adapted to capillary EE (cEE) to be able to analyze large urine sample series, and it was coupled online to LC-MS. cEE-LC-MS of acylcarnitines was optimized and characterized. The recovery, linearity, repeatability, and detection limit of the cEE-LC-MS method was good to excellent. To demonstrate the versatility of EE for sample preparation in analytical procedures, extracts were injected into a CZE-MS system, resulting in detection of the acylcarnitines along with more than 100 presumed metabolite peaks. The results presented here indicate that EE can be used as a fast sample preconcentration technique of low abundant urine metabolites, in combination with both LC and CZE.

Traditional processing strongly affects metabolite composition by hydrolysis in Rehmannia glutinosa roots.

The processing of biological raw materials is considered to have an important role in the therapeutic application in Traditional Chinese Medicine. The root of Rehmannia glutinosa has to be processed by nine cycles of rice wine immersing, steaming and drying before using in clinical applications. In order to understand the chemical changes resulting from the processing, a comprehensive analysis of Rehmanniae radix was made using (1)H-NMR and Fourier transform (FT)-mass spectrometry in combination with multivariate data analysis. After (1)H-NMR and principle component analysis, hydrolysis was found to be the major chemical process during the treatments. Catalpol, raffinose and stachyose levels gradually decreased during processing, whereas monosaccharides including galactose and glucose were found to be higher in processed roots. The metabolic profile changed gradually through the processing cycles although the differences became smaller after the fifth processing cycle. The positive and negative ion-mode mass spectra by high resolution FT-MS revealed several series of ion clusters with mass differences of 162.053 Da, indicating a difference of a hexose moiety. During the processing, the number and signal intensity of the smaller glycosides were increased. Therefore, these results indicate that the fresh Rehmanniae radix is rich in polysaccharides, which are hydrolyzed during the processing.

Endocrine pulse identification using penalized methods and a minimum set of assumptions.

The detection of hormone secretion episodes is important for understanding normal and abnormal endocrine functioning, but pulse identification from hormones measured with short interval sampling is challenging. Furthermore, to obtain useable results, the model underlying hormone secretion and clearance must be augmented with restrictions based on biologically acceptable assumptions. Here, using the assumption that there are only a few time points at which a hormone is secreted, we used a modern penalized nonlinear least-squares setup to select the number of secretion events. We did not assume a particular shape or frequency distribution for the secretion pulses. Our pulse identfication method, VisPulse, worked well with luteinizing hormone (LH), cortisol, growth hormone, or testosterone. In particular, applying our modeling strategy to previous LH data revealed a good correlation between the modeled and measured LH hormone concentrations, the estimated secretion pattern was sparse, and the small and structureless residuals indicated a proper model with a good fit. We benchmarked our method to AutoDecon, a commonly used hormone secretion model, and performed releasing hormone infusion experiments. The results of these experiments confirmed that our method is accurate and outperforms AutoDecon, especially for detecting silent periods and small secretion events, suggesting a high-secretion event resolution. Method validation using (releasing hormone) infusion data revealed sensitivities and selectivities of 0.88 and 0.95 and of 0.69 and 0.91 for VisPulse and AutoDecon, respectively.

Equating, or correction for between-block effects with application to body fluid LC-MS and NMR metabolomics data sets.

Combination of data sets from different objects (for example, from two groups of healthy volunteers from the same population) that were measured on a common set of variables (for example, metabolites or peptides) is desirable for statistical analysis in "omics" studies because it increases power. However, this type of combination is not directly possible if nonbiological systematic differences exist among the individual data sets, or "blocks". Such differences can, for example, be due to small analytical changes that are likely to accumulate over large time intervals between blocks of measurements. In this article we present a data transformation method, that we will refer to as "quantile equating", which per variable corrects for linear and nonlinear differences in distribution among blocks of semiquantitative data obtained with the same analytical method. We demonstrate the successful application of the quantile equating method to data obtained on two typical metabolomics platforms, i.e., liquid chromatography-mass spectrometry and nuclear magnetic resonance spectroscopy. We suggest uni- and multivariate methods to evaluate similarities and differences among data blocks before and after quantile equating. In conclusion, we have developed a method to correct for nonbiological systematic differences among semiquantitative data blocks and have demonstrated its successful application to metabolomics data sets.

Online capillary liquid-liquid electroextraction of peptides as fast pre-concentration prior to LC-MS.

In this research paper, we show that capillary electroextraction (cEE) is capable of fast online peptide concentration and that it can be coupled online to LC-MS to result in a fast and sensitive method. Electroextraction takes place when an electrical field is applied in a two-phase liquid-liquid system. Sample molecules in the organic phase migrate very fast into the aqueous phase and are concentrated in a small zone. In this work, cEE of peptides is developed and coupled online to LC-MS via a switching valve. Comparison of 10 min of cEE-LC-MS with a normal LC-MS injection showed more than 100-fold increased peak heights. Of five model peptides, good calibration curves in the range of 0.05-5 µmol/L were obtained. The linearity was good (R(2) values between 0.984 and 0.996) and RSD between 5% at the highest to 25% at the lowest concentration (n=3). The LOD of bradykinin, angiotensin I-converting enzyme inhibitor and angiotensin I was in the low nmol/L range. Analysis of a tryptic digest of eight model proteins resulted in more than 170 peptides, without bias for pI or hydrophilicity. Urine analysis is demonstrated, resulting in an LOD around 0.04 µmol/L urine for tryptic cytochrome C peptides spiked to urine and an increase of 42% in the number of chromatographic peaks compared with the conventional LC-MS. In summary, cEE-LC-MS is a fast electrophoresis-driven sample preconcentration technique that is quantitative, able to extract a wide peptide range and applicable to bioanalysis.

Effects of organically and conventionally produced feed on biomarkers of health in a chicken model.

Consumers expect organic products to be healthier. However, limited research has been performed to study the effect of organic food on health. The present study aimed to identify biomarkers of health to enable future studies in human subjects. A feeding experiment was performed in two generations of three groups of chickens differing in immune responsiveness, which were fed identically composed feeds from either organic or conventional produce. The animals of the second generation were exposed to an immune challenge and sacrificed at 13 weeks of age. Feed and ingredients were analysed on macro- and micronutrients, i.e. vitamins, minerals, trace elements, heavy metals and microbes. The chickens were studied by general health and immune parameters, metabolomics, genomics and post-mortem evaluation. The organic and conventional feeds were comparable with respect to metabolisable energy. On average, the conventionally produced feeds had a 10 % higher protein content and some differences in micronutrients were observed. Although animals on both feeds were healthy, differences between the groups were found. The random control group of chickens fed conventional feed showed overall a higher weight gain during life span than the group on organic feed, although feed intake was mostly comparable. The animals on organic feed showed an enhanced immune reactivity, a stronger reaction to the immune challenge as well as a slightly stronger 'catch-up growth' after the challenge. Biomarkers for future research were identified in the parameters feed intake, body weight and growth rate, and in immunological, physiological and metabolic parameters, several of these differing most pronounced after the challenge.

Systems biology-based diagnostic principles as pillars of the bridge between Chinese and Western medicine.

Innovative systems approaches to develop medicine and health care are emerging from the integration of Chinese and Western medicine strategies, philosophies and practices. The two medical systems are highly complementary as the reductionist aspects of Western medicine are favourable in acute disease situations and the holistic aspects of Chinese medicine offer more opportunities in chronic conditions and for prevention. In this article we argue that diagnosis plays a key role in building the bridge between Chinese and Western medicine. Recent advances in the study of health, healing, placebo effects and patient-physician interactions will be discussed pointing out the development of a system-based diagnosis. Especially, a system biology-based diagnosis can be used to capture phenotype information, leading towards a scientific basis for a more refined patient characterization, new diagnostic tools and personalized heath strategies. Subtyping of rheumatoid arthritis patients based on Chinese diagnostic principles is discussed as an example. New insights from this process of integrating Western and Chinese medicine will pave the way for a patient-centred health care ecosystem.

Improved cholesterol phenotype analysis by a model relating lipoprotein life cycle processes to particle size.

Increased plasma cholesterol is a known risk factor for cardiovascular disease. Lipoprotein particles transport both cholesterol and triglycerides through the blood. It is thought that the size distribution of these particles codetermines cardiovascular disease risk. New types of measurements can determine the concentration of many lipoprotein size-classes but exactly how each small class relates to disease risk is difficult to clear up. Because relating physiological process status to disease risk seems promising, we propose investigating how lipoprotein production, lipolysis, and uptake processes depend on particle size. To do this, we introduced a novel model framework (Particle Profiler) and evaluated its feasibility. The framework was tested using existing stable isotope flux data. The model framework implementation we present here reproduced the flux data and derived lipoprotein size pattern changes that corresponded to measured changes. It also sensitively indicated changes in lipoprotein metabolism between patient groups that are biologically plausible. Finally, the model was able to reproduce the cholesterol and triglyceride phenotype of known genetic diseases like familial hypercholesterolemia and familial hyperchylomicronemia. In the future, Particle Profiler can be applied for analyzing detailed lipoprotein size profile data and deriving rates of various lipolysis and uptake processes if an independent production estimate is given.

Feasibility of electrodialysis as a fast and selective sample preparation method for the profiling of low-abundant peptides in biofluids.

Considerable interest exists in endogenous peptides as potential biomarkers, since they act as signaling molecules and are formed by degradation of proteins. A crucial step in the profiling of these peptides is the sample preparation, which aims to enrich the low-abundant peptides, while removing interfering matrix compounds. In a feasibility study we examined the suitability of electrodialysis (ED) for this purpose. A custom-made device was developed from the low-binding material Kel-F. It consisted of two compartments separated by a dialysis membrane, over which a voltage was applied. One compartment served as donor (containing the sample), while the smaller acceptor compartment collected the peptides. The procedure was optimized by investigating the effect of the applied voltage, ammonium acetate buffer concentration, and ED duration using model peptides. Optimum conditions were found at 300 V (150 V/cm), 25 mM ammonium acetate buffer (pH 3.8) containing 20% v/v DMSO, and 10 min, respectively. With these optimized parameters, recoveries for the model peptides were found to be 35-85% (average 64%). Additionally, ED was successfully applied to the challenging synovial fluid biological sample (due to its high viscosity). In a synovial fluid sample from a rheumatoid arthritis patient, 27 peptides originating from 12 proteins were identified, of which a considerable fraction was not identified before with other methods. This demonstrates the usefulness and complementary nature of combining ED with nanoLC-MS for biomarker discovery. These results indicate that ED is promising as a fast and selective sample preparation method for the profiling of endogenous peptides.

Systems biology guided by Chinese medicine reveals new markers for sub-typing rheumatoid arthritis patients.

BACKGROUND: Complex chronic diseases such as rheumatoid arthritis have become a major challenge in medicine and for the pharmaceutical industry. New impulses for drug development are needed. OBJECTIVE: : A systems biology approach is explored to find subtypes of rheumatoid arthritis patients enabling a development towards more personalized medicine. METHODS: Blood samples of 33 rheumatoid arthritis (RA) patients and 16 healthy volunteers were collected. The RA patients were diagnosed according to Chinese medicine (CM) theory and divided into 2 groups, the RA Heat and RA Cold group. CD4 T-cells were used for a total gene expression analysis. Metabolite profiles were measured in plasma using gas chromatography/mass spectrometry. Multivariate statistics was employed to find potential biomarkers for the RA Heat and RA Cold phenotype. A comprehensive biologic interpretation of the results is discussed. RESULTS: : The genomics and metabolomics analysis showed statistically relevant different gene expression and metabolite profiles between healthy controls and RA patients as well as between the RA Heat and RA Cold group. Differences were found in the regulation of apoptosis. In the RA Heat group caspase 8 activated apoptosis seems to be stimulated while in the RA Cold group apoptosis seems to be suppressed through the Nrf2 pathway. CONCLUSIONS: RA patients could be divided in 2 groups according to CM theory. Molecular differences between the RA Cold and RA Heat groups were found which suggest differences in apoptotic activity. Subgrouping of patients according to CM diagnosis has the potential to provide opportunities for better treatment outcomes by targeting Western or CM treatment to specific groups of patients.

Role of amino acids in rheumatoid arthritis studied by metabolomics.

BACKGROUND: Rheumatoid arthritis (RA) is a complex, chronic autoimmune disease characterized by various inflammatory symptoms, including joint swelling, joint pain, and both structural and functional joint damage. The most commonly used animal model for studying RA is mice with collagen-induced arthritis (CIA); the wide use of this model is due primarily to many similarities with RA in human patients. Metabolomics is used increasingly in biological studies for diagnosing disease and for predicting and evaluating drug interventions, as a large number of disease-associated metabolites can be analyzed and interpreted from a biological perspective. AIM: To profile free amino acids and their biogenic metabolites in CIA mice plasma. METHOD: Ultra-high-performance liquid chromatography/tandem mass spectrometry coupled with multiple reaction monitoring (MRM) was used for metabolomics study. RESULTS: Profile of 45 amine metabolites, including free amino acids and their biogenic metabolites in plasma was obtained from CIA mice. We found that the plasma levels of 20 amine metabolites were significantly decreased in the CIA group. CONCLUSION: The results suggest that a disordered amine response is linked to RA-associated muscle wasting and energy expenditure.

A Bridge of Light: Toward Chinese and Western Medicine Perspectives Through Ultraweak Photon Emissions.

The gap between Western medicine and traditional Chinese medicine (CM) is closely related to the diversity in culture, philosophy, and scientific developments. Although numerous studies have evaluated the efficacy of acupuncture, the gap in explanatory disease models has not been bridged so far. Developments in research of ultraweak photon emission (UPE) and organized dynamics of metabolism and its relationship with technological advances in metabolomics have created the conditions to bring the basics of the medicines of the West and East together which might open the avenue for a scientific dialogue. The paper discusses (1) the UPE in relation to Qi energy, meridians and acupuncture points in CM, (2) the biochemical explanation of photon emission of living systems in Western biomedicine, and (3) the progress in research on the large-scale organization and dynamics of the metabolic network including photon metabolism.

Similarities and differences in lipidomics profiles among healthy monozygotic twin pairs.

Differences in genetic background and/or environmental exposure among individuals are expected to give rise to differences in measurable characteristics, or phenotypes. Consequently, genetic resemblance and similarities in environment should manifest as similarities in phenotypes. The metabolome reflects many of the system properties, and is therefore an important part of the phenotype. Nevertheless, it has not yet been examined to what extent individuals sharing part of their genome and/or environment indeed have similar metabolomes. Here we present the results of hierarchical clustering of blood plasma lipid profile data obtained by liquid chromatography-mass spectrometry from 23 healthy, 18-year-old twin pairs, of which 21 pairs were monozygotic, and 8 of their siblings. For 13 monozygotic twin pairs, within-pair similarities in relative concentrations of the detected lipids were indeed larger than the similarities with any other study participant. We demonstrate such high coclustering to be unexpected on basis of chance. The similarities between dizygotic twins and between nontwin siblings, as well as between nonfamilial participants, were less pronounced. In a number of twin pairs, within-pair dissimilarity of lipid profiles positively correlated with increased blood plasma concentrations of C-reactive protein in one twin. In conclusion, this study demonstrates that in healthy individuals, the individual genetic background contributes to the blood plasma lipid profile. Furthermore, lipid profiling may prove useful in monitoring health status, for example, in the context of personalized medicine.