Background High throughput study of metabolic pathways might help identify new biomarkers and therapeutic targets in autoimmune diseases. Primary Sjögren9s syndrome (pSS) currently lacks prognostic biomarkers and efficacious and specific treatments. We therefore assessed serum levels of 35 metabolites in pSS using high-resolution magic-angle spinning (HRMAS) proton magnetic resonance spectroscopy. Methods The blood samples of 194 patients with pSS enrolled in the prospective multicenter ASSESS cohort and 41 blood donors were analysed in this study. After cryopreservation at -80°C, the samples were studied with HRMAS proton magnetic resonance spectroscopy (1H-MRS). Spectra were recorded on a Bruker Avance III 500 spectrometer operating at a proton frequency of 500 MHz. All the 1D NMR spectra were acquired during 76 min. Supervised clustering was performed on the spectral region between 0.5 and 4.7 ppm using partial least square discriminant analysis (PLS-DA). Results Supervised clustering of the 194 samples allowed to discriminate all patients with pSS from healthy controls (R2Y=0.88 and Q2=0.86 (figure 1)). Interestingly, 4 serum metabolites were significantly increased in pSS compared to healthy controls: threonine, lactate, glutamine and acetate. 6 metabolites were significantly decreased in pSS compared to healthy controls: myo-inositol, creatine, lysine, aspartate, glutamate and alanine Conclusions This first high-throughput analysis of metabolic pathways disclosed a specific metabolomic signature of pSS allowing discriminating all patients with pSS from controls. This new and very potent means of metabolic analysis may help to increase our knowledge on the pathogenesis of pSS, identify biomarkers, and new therapeutic targets. Disclosure of Interest None declared

A new analytical method that allows the rapid assessment of fish freshness and quality is presented. The method is based on 1 H high-resolution magic angle spinning (HR-MAS) NMR spectroscopy and allows the rapid determination of two well-established indicators of fish freshness and quality: the K value and the trimethylamine nitrogen (TMA-N) content. The method is demonstrated on four different species of fish (sea bream, sea bass, trout, and red mullet) stored on ice at 0 °C. The results obtained are in agreement with more cumbersome methods classically used to determine the K value and the TMA-N concentration. The main advantage of the 1 H HR-MAS NMR approach is to allow a direct measurement of these two parameters directly on unprocessed fish sample without using any preliminary extraction. The total analysis time, including sample preparation, is of the order of 40 min per sample.

BACKGROUND:Neuromyelitis optica (NMO) and multiple sclerosis (MS), two inflammatory demyelinating diseases, are characterized by different therapeutic strategies. Currently, the only biological diagnostic tool available to distinguish NMO from MS is the specific serum autoantibody that targets aquaporin 4, but its sensitivity is low.OBJECTIVE:To assess the diagnostic accuracy of metabolomic biomarker profiles in these two neurological conditions, compared to control patients.METHODS:We acquired serum spectra (47 MS, 44 NMO and 42 controls) using proton nuclear magnetic resonance ((1)H-NMR) spectroscopy. We used multivariate pattern recognition analysis to identify disease-specific metabolic profiles.RESULTS:The (1)H-NMR spectroscopic analysis evidenced two metabolites, originating probably from astrocytes, scyllo-inositol and acetate, as promising serum biomarkers of MS and NMO, respectively. In 87.8% of MS patients, scyllo-inositol increased 0.15 to 3-fold, compared to controls and in 74.3% of NMO patients, acetate increased 0.4 to 7-fold, compared to controls. Using these two metabolites simultaneously, we can discriminate MS versus NMO patients (sensitivity, 94.3%; specificity, 90.2%).CONCLUSION:This study demonstrates the potential of (1)H-NMR spectroscopy of serum as a novel, promising analytical tool to discriminate populations of patients affected by NMO or MS.

OBJECTIVE: The aim of the study was to assess the diagnostic accuracy of metabolomic biomarker profiles by 1H high-resolution magic angle spinning nuclear magnetic resonance (HRMAS-NMR) spectroscopy in these two diseases compared to control subjects. BACKGROUND: Differential diagnosis between Neuromyelitis Optica (NMO) and Multiple Sclerosis (MS) is a crucial point given the different therapeutical approach for these two diseases. Actually, the only biological diagnostic tool available is the specific serum auto-antibody NMO-IgG but its sensitivity is relatively low. DESIGN/METHODS: 47 patients, 44 NMO patients and 42 healthy subjects were included in this study. For each serum sample a NMR spectrum was acquired using Bruker 500 MHz spectrometer. The spectral region between 4.7 and 0.5 ppm of each spectrum was binned into regions of 0.01 ppm (AMIX, Bruker). The data sets were analyzed using partial least square discriminant analysis (PLS-DA) in order to build a statistical model that optimizes the separation between the groups of subjects. RESULTS: A PLS-DA analysis revealed a clear separation between the and control groups (R2Y = 0.84, Q2= 0.68), between NMO and controls (R2Y = 0.77, Q2= 0.72) and between and NMO (R2Y = 0.85, Q2= 0.8). We found that two metabolites were important for a good discrimination between these 3 groups: Scyllo-Inositol which allows classifying a pathologic serum sample as or NMO with an accuracy of 75.2 % and acetate which allows classifying a non MS serum sample as NMO or healthy with an accuracy of 87.9%. CONCLUSIONS: We demonstrate the usefulness of 1H HRMAS NMR spectroscopy as a novel analytical tool to discriminate between these two close neurological diseases. The next step will be the validation of these two potential biomarkers on a more important cohort of patients and then the determination of a cut-off value for the respective serum concentrations corresponding to these metabolites. Disclosure: Dr. Chanson has nothing to disclose. Dr. Moussallieh has nothing to disclose. Dr. Elbayed has nothing to disclose. Dr. Rudolf has nothing to disclose. Dr. Piotto has nothing to disclose. Dr. Namer has nothing to disclose. Dr. De Seze has received personal compensation for activities with Allergan, Inc., Almirall, Bayer Schering, Biogen Idec, Genzyme Corporation, LFB, Merck Serono, Sanofi-Aventis Pharmaceuticals, Inc., and Teva Neuroscience.

Si la lésion typique de SEP est la plaque focale en substance blanche, elle est visualisée en IRM par un hypersignal-T2 et en pathologie par un infiltrat périveinulaire de cellules mononucléées inflammatoire associée à une démyélinisation et parfois de la perte axonale. Dans cette lésion focale les lymphocytes, surtout T CD8+ sont largement représentés associés à de nombreux macrophages phagocytant la myéline pour la dégrader. Cette maladie inflammatoire démyélinisante et dégénérative chronique et évolutive associe précocement dans la maladie mais de façon plus marquée au fur et à mesure du temps une inflammation diffuse du système nerveux central, piégée dans le tissu, avec une barrière hémato-encéphalique en tout cas non rompue de façon évidente. Cette inflammation chronique associe aux cellules lymphocytaires une microglie activée majeure. Ainsi, l'inflammation reste la caractéristique clef aussi bien dans les formes rémittentes que dans les formes progressives primaires et secondairement progressives. Dans ces dernières formes l'inflammation reste liée aux différents paramètres de démyélinisation.The basic hallmark of multiple sclerosis pathology is the focal demyelinated plaque; it is visible as a focal T2-hypersignal lesion on MRI and under microscopy perivenular mononuclear cells infiltrates are described associated with demyelination with partial axonal loss. In that focal lesion, lymphocytes and especially CD8+ T cells are well represented but B cells can be found, outnumbered by macrophages with myelin debris. MS is a an inflammatory demyelinating and degenerative chronic and evolving disease where a diffuse inflammation in the tissue is also described early but is more and more prominent over time. This diffuse inflammation in white and grey matter is trapped in the parenchyma without any evident disruption of the blood brain barrier. That chronic diffuse and trapped inflammation is characterized by a prominent activated microglia. Indeed, inflammation remains the key feature in relapsing remitting form as well as in secondary or primary progressive form of MS, and inflammation stay related to the demyelination and axonal loss parameters.

Scot15® is a low-K+ preservation solution including polyethylene glycol (PEG) as a colloid for protection of endothelium during cold ischemia. PEG was previously demonstrated to have “immunocamouflage” properties. The aim of this study was to assess whether these properties would be beneficial in a pig lung transplant model in comparison to Perfadex® as golden standard solution.

In 1970s, taurine deficiency was reported to induce photoreceptor degeneration in cats and rats. Recently, we found that taurine deficiency contributes to the retinal toxicity of vigabatrin, an antiepileptic drug. However, in this toxicity, retinal ganglion cells were degenerating in parallel to cone photoreceptors. The aim of this study was to re-assess a classic mouse model of taurine deficiency following a treatment with guanidoethane sulfonate (GES), a taurine transporter inhibitor to determine whether retinal ganglion cells are also affected. GES treatment induced a significant reduction in the taurine plasma levels and a lower weight increase. At the functional level, photopic electroretinograms were reduced indicating a dysfunction in the cone pathway. A change in the autofluorescence appearance of the eye fundus was explained on histological sections by an increased autofluorescence of the retinal pigment epithelium. Although the general morphology of the retina was not affected, cell damages were indicated by the general increase in glial fibrillary acidic protein expression. When cell quantification was achieved on retinal sections, the number of outer/inner segments of cone photoreceptors was reduced (20 %) as the number of retinal ganglion cells (19 %). An abnormal synaptic plasticity of rod bipolar cell dendrites was also observed in GES-treated mice. These results indicate that taurine deficiency can not only lead to photoreceptor degeneration but also to retinal ganglion cell loss. Cone photoreceptors and retinal ganglion cells appear as the most sensitive cells to taurine deficiency. These results may explain the recent therapeutic interest of taurine in retinal degenerative pathologies.

High-resolution magic angle spinning (HRMAS) Nuclear magnetic resonance (NMR) 1H spectroscopy is playing an increasingly important role for diagnosis. This technique enables setting up metabolite profiles of ex vivo pathological and healthy tissue. Automatic quantitation of HRMAS signals provides reliable reference profiles useful to monitor diseases and pharmaceutical follow-up. However for several metabolites, the values of chemical shifts of proton groups may slightly differ according to the microenvironment in the tissue or cells, in particular to its pH. This hampers accurate estimation of the metabolite concentrations mainly when using quantitation algorithms based on a metabolite basis-set: the metabolite fingerprints are not correct anymore. In this work, we propose an accurate method based on quantum mechanical (QM) simulations. The proposed algorithm automatically corrects mismatches between the signal under analysis and the signals of the simulated basic-set by modifying the basis-set signals. In the optimization procedure, the basis-set signals are simulated again by varying the chemical shifts of metabolites in the QM procedure. Cross-correlation was used as cost function to measure how well the signals match each other. The proposed method, QM-QUEST, provides more robust fitting while limiting user involvement and respects the correct fingerprints of metabolites. Its efficiency is demonstrated by accurately quantitating signals from tissue samples of human brains with oligodendroglioma. (C) 2011 Elsevier Masson SAS. All rights reserved.

Objectives . The objectives of the present study are to determine if a metabolomic study by HRMAS-NMR can (i) discriminate between different histological types of epithelial ovarian carcinomas and healthy ovarian tissue, (ii) generate statistical models capable of classifying borderline tumors and (iii) establish a potential relationship with patient's survival or response to chemotherapy. Methods . 36 human epithelial ovarian tumor biopsies and 3 healthy ovarian tissues were studied using 1 H HRMAS NMR spectroscopy and multivariate statistical analysis. Results . The results presented in this study demonstrate that the three histological types of epithelial ovarian carcinomas present an effective metabolic pattern difference. Furthermore, a metabolic signature specific of serous (N-acetyl-aspartate) and mucinous (N-acetyl-lysine) carcinomas was found. The statistical models generated in this study are able to predict borderline tumors characterized by an intermediate metabolic pattern similar to the normal ovarian tissue. Finally and importantly, the statistical model of serous carcinomas provided good predictions of both patient's survival rates and the patient's response to chemotherapy. Conclusions . Despite the small number of samples used in this study, the results indicate that metabolomic analysis of intact tissues by HRMAS-NMR is a promising technique which might be applicable to the therapeutic management of patients.

A. Lazariev, A-R. Allouche, M. Aubert-Frécon, F. Fauvelle, K. Elbayed, M. Piotto, I. J. Namer, D. van Ormondt, and D. Graveron-Demilly Creatis-LRMN, Université Claude Bernard Lyon 1, Villeurbanne, France, LASIM, Université Claude Bernard Lyon 1, Villeurbanne, France, CRSSA/BCM, Grenoble, France, Institut de Chimie, Strasbourg, France, Bruker BioSpin, Wissembourg, France, Department of Biophysics and Nuclear Medicine, University Hospitals of, Strasbourg, France, Delft University of Technology, Delft, Netherlands

High resolution magic-angle spinning (HRMAS) NMR spectroscopy is a well established technique for ex vivo metabolite investigations but experimental factors such as ischemic delay or mechanical stress due to continuous spinning deserve further investigations. Cortical brain samples from rats that underwent ultrafast in vivo microwave irradiation (MWp group) were compared to similar samples that underwent standard nitrogen freezing with and without exposure to domestic microwaves (FN and FN+MWd groups). One dimensional (1)H HRMAS NMR spectra were acquired and 16 metabolites of interest were quantified. Within each group 3 samples underwent long lasting acquisition (up to 15 h). Statistically significant differences in metabolite concentrations were observed between groups for metabolites associated to post mortem biochemical changes and/or anaerobic glycolysis including several neurotransmitters. Spectral assessment over time showed a drastic reduction of biochemical variations in both MW groups. Only 2/16 metabolites exhibited significant signal variations after 15 h of continuous spinning and acquisition in the MWp group. This number increased to 10 in the FN group. We confirmed limited anaerobic metabolism and post mortem degradation after ultra fast in vivo MW irradiation. Furthermore, spectra obtained after MWp and MWd irradiation exhibited an extremely stable spectral pattern over extended periods of continuous acquisition.

High-resolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR) is playing an increasingly important role for diagnosis. This technique enables setting up metabolite profiles of ex vivo pathological and healthy tissue. The need to monitor diseases and pharmaceutical follow-up requires an automatic quantitation of HRMAS 1H signals. However, for several metabolites, the values of chemical shifts of proton groups may slightly differ according to the micro-environment in the tissue or cells, in particular to its pH. This hampers the accurate estimation of the metabolite concentrations mainly when using quantitation algorithms based on a metabolite basis set: the metabolite fingerprints are not correct anymore. In this work, we propose an accurate method coupling quantum mechanical simulations and quantitation algorithms to handle basis-set changes. The proposed algorithm automatically corrects mismatches between the signals of the simulated basis set and the signal under analysis by maximizing the normalized cross-correlation between the mentioned signals. Optimized chemical shift values of the metabolites are obtained. This method, QM-QUEST, provides more robust fitting while limiting user involvement and respects the correct fingerprints of metabolites. Its efficiency is demonstrated by accurately quantitating 33 signals from tissue samples of human brains with oligodendroglioma, obtained at 11.7 tesla. The corresponding chemical shift changes of several metabolites within the series are also analyzed.

High-resolution magic angle spinning (HRMAS) 1H spectroscopy is playing an increasingly important role for diagnosis. This technique enables setting up metabolite profiles of ex vivo pathological and healthy tissue. Automatic quantitation of HRMAS signals provides reliable reference profiles to monitor diseases and pharmaceutical follow-up. Nevertheless, for several metabolites chemical shifts may slightly differ according to the micro-environment in the tissue or cells, in particular its pH. This hampers accurate estimation of the metabolite concentrations mainly when using quantitation algorithms based on a metabolite basis-set. In this work, we propose a user-friendly way to circumvent this problem based on stretching of the metabolite basis-set signals and maximization of the correlation between the HRMAS and basis-set spectra prior to quantitation.

A. BELGHITH, C. COLLET, K. ELBAYED, L. RUMBACH, I. NAMER, and J-P. ARMSPACH University of Strasbourg, LSIIT CNRS UMR 7005, Strasbourg, Alsace, France, University of Strasbourg, LSIIT CNRS UMR 7005, France, University of Strasbourg, Institut de Chimie, Neurology Department CHU Minjoz Besancon -France, University of Strasbourg, LINC CNRS FRE 3289 France, University of Strasbourg, LINC CNRS FRE 3289, France

A. Lazariev, F. Fauvelle, M. Piotto, K. Elbayed, J. Namer, D. van Ormondt, and D. Graveron-Demilly Laboratoire Creatis-LRMN; CNRS UMR 5220; INSERM U630; INSA de Lyon, Université Claude Bernard Lyon 1, Villeurbanne, France, CRSSA/BCM, Grenoble, France, Bruker BioSpin, Wissembourg, France, Institut de Chimie, Strasbourg, France, Department of Biophysics and Nuclear Medicine, University Hospitals of Strasbourg, Strasbourg, France, Delft University of Technology, Delft, Netherlands

Colorectal cancer is one of the most frequent and most lethal forms of cancer in the western world. The aim of this study is to characterize by 1 H high resolution magic angle spinning NMR spectroscopy (HRMAS) the metabolic fingerprint of both tumoral and healthy tissue samples obtained from a cohort of patients affected by primary colorectal adenocarcinoma. By analyzing HRMAS data using multivariate statistical analysis (PLS-DA), the two types of tissues could be discriminated with a high level of confidence. The identification of the metabolites at the origin of this discrimination revealed that adenocarcinomas are richer in taurine, glutamate, aspartate, and lactate whereas healthy tissues contain a higher amount of myo-inositol and β-glucose. The statistical model resulting from the PLS-DA analysis was subsequently used to perform a blind test on tumoral and healthy colon biopsies. The results of the classification showed that the HRMAS analysis has very high sensitivity and specificity.

In spite of having been the object of considerable attention, the histopathological grading of oligodendrogliomas is still controversial. The determination of reliable biomarkers capable of improving the malignancy grading remains an essential step in working toward better therapeutic management of patients. Therefore the metabolome of 34 human brain biopsies, histopathologically classified as low‐grade (LGO, N = 10) and high‐grade (HGO, N = 24) oligodendrogliomas, was studied using high‐resolution magic angle spinning nuclear magnetic resonance spectroscopy (HRMAS NMR) and multivariate statistical analysis. The classification model obtained afforded a clear distinction between LGOs and HGOs and provided some useful insights into the different metabolic pathways that underlie malignancy grading. The analysis of the most discriminant metabolites in the model revealed the presence of tumoral hypoxia in HGOs. The statistical model was then used to study biopsy samples that were classified as intermediate oligodendrogliomas ( N = 6) and glioblastomas (GBMs) ( N = 30) by histopathology. The results revealed a gradient of tumoral hypoxia increasing in the following direction: LGOs, intermediate oligodendrogliomas, HGOs, and GBMs. Moreover upon analysis of the clinical evolution of the patients, the metabolic classification seems to provide a closer correlation with the actual patient evolution than the histopathological analysis. Magn Reson Med 59:959–965, 2008. © 2008 Wiley‐Liss, Inc.