**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

BIOMEDICAL

P-47

Serum and tissue metabolomics for assessment of treatment response and survival of breast cancer patients

PRESENTING AUTHOR: Julia Debik, Department of Circulation and Medical Imaging - MR Center, Faculty of Medicine and Health Sciences, Norway

CO-AUTHORS: Leslie R. Euceda, Steinar Lundgren, Olav Engebraaten, Øystein Garred, Hedda von der Lippe Gythfeldt, Tone F. Bathen, Guro F. Giskeødegård

While tissue metabolomics reveals the direct effect of treatment, serum metabolomics shows a snapshot of the metabolic state of the host organism, affected by factors such as diet, age and treatment, in addition to the tumor itself. The aim of this study is to characterize the metabolic profile in breast cancer patients receiving neoadjuvant chemotherapy (N=132) and to relate metabolic changes to treatment response and survival. Half of the patients were randomized to receive bevacizumab (antiangiogenic drug) in addition to standard chemotherapy, and tumor biopsies and serum were collected prior to and during treatment. All samples were analyzed by nuclear magnetic resonance spectroscopy (NMR). Multilevel partial least squares discriminant analysis (multilevel PLS-DA) showed clear changes in serum metabolite levels during treatment (p-values ≤ 0.01). Increased levels of isoleucine and decreased levels of creatine, creatinine, histidine and ornithine, in addition to unfavorable changes in lipid levels were observed between pre- and on-treatment samples. Bevacizumab treatment and poor response (patients with residual cancer burden (RCB) index 3) were associated with the serum metabolic profile (accuracies = 64%, 64%; p-values = 0.014, 0.049, respectively). Five-year survival could be predicted from metabolic profiles in tissue (accuracy = 72%; p-value = 0.005), but not serum. Low correlations between serum and tissue metabolites were observed, revealing the complementary nature of the metabolic information in these biological matrices. Collectively, our results demonstrate a potential clinical application of serum and tissue metabolomics for patient-monitoring during and after treatment, further indicating potential for NMR in assessment of patient outcome.

P-48

A Coupled Lipidomics-Machine Learning Approach for Early Diagnosis of clear cell Renal Cell Carcinoma

PRESENTING AUTHOR: María Monge, CIBION-CONICET, Argentina

CO-AUTHORS: Malena Manzi, Martín Palazzo, Nicolás Zabalegui, María Elena Knott, Pierre Beauseroy, Patricio Yankilevich, María Isabel Giménez

Clear cell (ccRCC) is the most common (75%) lethal subtype of RCC, and is considered a glycolytic and lipogenic tumor. More than 30% of patients, often incidentally diagnosed by imaging procedures, exhibit locally advanced or metastatic RCC at the time of diagnosis and the disease is inherently resistant to chemotherapy and radiotherapy. In this work, serum samples from a cohort that included patients with different ccRCC stages (SI, SII, SIII and, SIV; n=112) and controls (n=52) were interrogated with a discovery-based lipidomics approach using ultraperformance liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry and machine learning methods. Support vector machine models and the least absolute shrinkage and selection operator (Lasso) variable selection method yielded two discriminant panels for ccRCC detection and early diagnosis. A first 18-feature panel allowed discriminating ccRCC patients from controls with 96.8% accuracy in a training set under cross-validation, and 81.4% accuracy in an independent test set. Fifteen features of the panel were significantly decreased in ccRCC after correcting for multiple testing. A second model was trained to discriminate early stages (I-II) from late stages (III-IV) ccRCC and provided a 26-feature panel that allowed sample classification with 84.5% accuracy in the training set under cross-validation, and 82.1% accuracy in the classification of stage I ccRCC patients from an independent test set. Current work involves feature identification in both panels by accurate mass, isotopic pattern, tandem MS experiments, and chemical standard analysis. Results are auspicious for early ccRCC diagnosis after validation of the panels in larger and different cohorts.

P-49

Untargeted metabolomics study of urine and plasma samples in prostate cancer patients

PRESENTING AUTHOR: Wiktoria Struck-Lewicka, Medical University of Gdansk, Poland

CO-AUTHORS: Małgorzata Patejko, Renata Wawrzyniak, Marta Kordalewska, Danuta Siluk, Marcin Markuszewski, Marcin Matuszewski, Michał Markuszewski

Prostate Cancer (CaP) is the second most common type of cancer and the third leading cause of cancer death in men. Despite its common occurrence and high mortality rate, the currently used CaP biomarkers are still not enough specific and selective. Therefore, there is an urgent need for searching cancer related metabolites that would support in explaining pathogenesis of the disease and can be considered as potential markers in CaP recognition. In this project, we performed analyses of metabolic fingerprints from plasma and urine samples derived from prostate cancer patients (n= 40) and healthy volunteers (n=43). The determinations were utilized using complementary analytical techniques, namely gas chromatography (GC-EI-QqQ/MS) and liquid chromatography (LC-ESI-TOF/MS) both coupled with mass spectrometry detection. Each data set was pre-processed, filtered and aligned. Next, the univariate and multivariate statistical analyses were carried out for selection of statistically significant metabolites (FDR p value <0.05) and subsequently in order to assess their prediction ability. Metabolites were putatively identified using several databases including HMDB, KEGG, Metlin and LipidMaps. The selected significantly altered metabolites that contribute the most into groups discrimination were mainly linked to amino acid, TCA cycle, FFA and purine and pyrimidine metabolism [1]. These results have to be further confirmed using targeted metabolomics approach. The work has been supported by the National Science Centre by the project no 2014/13/D/NZ7/00368.
*AWARD WINNERS

BIOMEDICAL

P-50 Unravelling altered RNA metabolism in pancreatic cancer and breast cancer cells by advanced mass spectrometric techniques

PRESENTING AUTHOR: Simon Lagies, Center for Biological Systems Analysis, University of Freiburg, Germany

CO-AUTHORS: Manuel Schlimpert, Lukas M. Braun, Michel Kather, Michael Rodamer, Thalia Erbes, Uwe A. Wittel, Bernd Kammerer

Modified nucleosides are a diverse class of chemically similar compounds where the common nucleosides bare additional functional groups such as methylations, acetylations or hydroxylations. They are produced under physiological conditions but are especially elevated in transformed cells or tissues. They cannot be recycled by the cellular salvage pathway and are therefore excreted to cell culture medium or body fluids. Here, we compare the profiles of excreted modified nucleosides in different pancreatic as well as breast cancer cell lines obtained by LC-QqQ or LC-IMS-HRMS analysis. Cluster analyses are capable of discriminating even different sub-types of these malignancies. Thus, monitoring modified nucleosides is of high potential in future cancer research.

P-51 Phenotyping of cellular senescence by 1H-NMR based metabolomics and hyperpolarized 13C-MRS

PRESENTING AUTHOR: Christoph Trautwein, University of Tuebingen, Werner Siemens Imaging Center, Germany

CO-AUTHORS: Marie-Aline Neveu, Ben Zhou, Marcel A. Krueger, Lars Zender, Andreas M. Schmid, Bernd J. Pichler

Senescence is a steady state of cell cycle arrest and an often observed phenomenon in cancer. While it can be seen as a stable end-point for the disease, still little is known about detailed mechanisms during therapy. The investigation of senescence metabolism may therefore help to develop new in-vivo markers and treatment approaches. In this study we investigated metabolic changes in different senescent cancer cell models using in-vitro hyperpolarized 1-13C-pyruvate MRS (7T) and ex-vivo 1H-NMR (600 MHz). Senescence was induced in human colon cancer cells (HCT116) by doxorubicin, in liver progenitor cells (HRas) by p53-reactivation and in a liver carcinoma cell line (HCC) by a ribosomal checkpoint inhibitor (RCI). Experiments with hyperpolarized 1-13C-pyruvate revealed a significantly decreased lactate production in RCI treated HCC cells without changes in alanine production. Interestingly, lactate and alanine metabolism were not impaired in senescent HCT116 cells. These findings are supported by results from 1H NMR data for metabolites of cell growth and energy storage. A 2-fold lactate/alanine increase and 3-fold phosphocholine/ glycerophosphocholine decrease was identified for HRas compared to HCT116 cells between control and senescence. By contrast, ratios of energy storage (phosphocreatine/creatinine) were similar between the two cell lines and applied therapy. Our first data suggest that senescence metabolism is influenced by treatment type as well as genotype. RCI inhibition and p53-reactivation impaired lactate production in HCC and HRas progenitor cells, respectively, while doxorubicin didn't in HCT116 cells where cell growth markers remained high. Further investigations of lipid metabolism and additional sampling time points are required.

P-52 One carbon metabolomics in cancer

PRESENTING AUTHOR: Matthias Schittmayer, OMICS Center Graz, Austria

CO-AUTHORS: Martin Pichler, Joerg Lindenmann, Luka Brcic, Nicola Zamboni, Ruth Birner-Gruenberger

One carbon metabolism is a limiting pathway in cellular proliferation as it is crucial for the biosynthesis of nucleotides. Therefore, one carbon metabolism has continuously been a major target of cancer chemotherapy from its beginning in the 1950s until the present day. Also, altered expression levels of individual one carbon metabolism enzymes have been reported as highly significant biomarkers of drug efficacy and disease free survival in various types of cancer. However, enzyme abundance is only an indirect readout of enzymatic activity and the resulting metabolome. So far, metabolic analysis of one carbon metabolism has been hampered by the low chemical stability and high interconvertibility of folate cofactors, which play a crucial role in the transfer of one carbon units. We have developed a complete workflow that employs simultaneous extraction and stabilization of folates by derivatization that allows a comprehensive assessment of metabolites in one carbon metabolism and the connected pathways. We now aim to apply this method on non-small cell lung carcinoma to classify individual tumors based on one carbon metabolism patterns and predict chemoresistance/sensitivity as well as tumor differentiation grade and invasiveness, to enable precision treatment.

P-53 Reactivation of Dihydroorotate Dehydrogenase-Driven Pyrimidine Biosynthesis Restores Tumor Growth of Respiration-Deficient Cancer Cells

PRESENTING AUTHOR: Sehyun Oh, Seoul National University, South Korea

CO-AUTHORS: Martina Bajzikova, Jaromira Kovarova, Ana R. Coelho, Stepana Boukalova

Cancer cells without mitochondrial DNA (mtDNA) do not form tumors unless they reconstitute oxidative phosphorylation (OXPHOS) by mitochondria acquired from host stroma. To understand why functional respiration is crucial for tumorigenesis, we used time-resolved analysis of tumor formation by mtDNA-depleted cells and genetic manipulations of OXPHOS. We show that pyrimidine biosynthesis dependent on respiration-linked dihydroorotate dehydrogenase (DHODH) is required to overcome cell-cycle arrest, while mitochondrial ATP generation is dispensable for tumorigenesis. Latent DHODH in mtDNA-deficient cells is fully activated with restoration of complex III/IV activity and coenzyme Q redox-cycling after mitochondrial transfer, or by introduction of an alternative oxidase. Further, deletion of DHODH interferes with tumor formation in cells with fully functional OXPHOS, while disruption of mitochondrial ATP synthase has little effect. Our results show that DHODH-driven pyrimidine biosynthesis is an essential pathway linking respiration to tumorigenesis, pointing to inhibitors of DHODH as potential anti-cancer agents.
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**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

BIOMEDICAL

P-54

In-vitro anticancer activity of Flower of Cassia alata L. on Human urinary bladder carcinoma (T24) cell line

PRESENTING AUTHOR: Meenakshi Barua, B.K. Birla College of Arts, Science and Commerce., India

CO-AUTHORS: Meeta Bhot

The present study investigated Cassia alata L. Flower plant fraction on human urinary bladder carcinoma (T24) cell lines via in-vitro SRB assay for anticancer property. Fresh flowers of Cassia alata (C. alata) plant were collected from suburban area of Maharashtra, India for preparation of plant extract via Soxlet extraction method. Bioactive fraction was separated via Column Chromatography method. Separated fraction was used against T24 carcinoma & Vero cell line (mammalian non cancerous cells) in four different concentration viz. 10, 20, 40, 80µg/ml. Effect was compared with Adriamycin (standard drug, used as positive control) and Emodin, a Plant standard. Separated plant fraction demonstrated a dose-dependent reduction in the overall activity of T-24 carcinoma cell line. C. alata flower separated fraction exhibited cytotoxic effect on T24 carcinoma cell line with IC50 value 45.3µg/ml and effective GI50 value 18.8µg/ml. Graph obtained from SRB cytotoxicity assay showed that separated plant fraction reduced the growth in T24 cell lines by lower than 50% with initial 10µg/ml concentration. In Vero cell line separated plant fraction and plant standard not showed any cytotoxic effect even when applied in higher concentration i.e. 80µg/ml. In contrast, standard anticancer drug showed pronounced cytotoxic effect even in lower concentration i.e. 10µg/ml. Phase contrast micrographs of T24 cell line treated with separated fraction showed significant decrease in viable cell numbers at 24 hrs of treatment. In conclusion, present study showed that separated fraction from C. alata flower has potential anticancer activity and showed significant result against Urinary bladder carcinoma cell line.

P-55

Colorectal Cancer : Biomarkers and Effect Size

PRESENTING AUTHOR: Nicolas Di Giovanni, University of Liège, MS Lab, Obiachem Group, Belgium

CO-AUTHORS: Meuwis Marie-Alice, Louis Edouard, Focant Jean-François

Colorectal cancer kills more than 700.000 persons each year worldwide. Nevertheless, its diagnosis is still largely based on invasive tissue sampling and gaps remain in the understanding of its pathogenesis, with complex combinations between lifestyle, genetics, epigenetics, chronic inflammation (IBD) and microbiota. We analyzed serum samples from patients affected by colorectal cancer (CRC, n = 18) and by colorectal cancer in remission (R-CRC, n = 17), and samples from healthy patients matched for biases (HC, n = 19 and R-HC, n = 17). The aim was to find candidate biomarkers able to diagnose the active state of the disease as well as to compare the concentration levels of the molecules of interest with the remission state to better understand the biolocal processes beneath the observed clinical and metabolic symptoms. To do so, an optimized and validated (NIST SRM 1950) comprehensive GC×GC-(HR)TOFMS method we developed was used. It includes an in-house QC system, data processing based on multiple statistical techniques and identification using full mass spectrum, linear retention indices and accurate mass provided by state-of-the-art high-resolution (HR) time-of-flight mass spectrometry. Because the experimental design prevented a direct comparison between the active and remission samples, which were not directly matched for biases, we used a measure called effect size that has the advantage to not only focus on statistical significance but on effect (here signal variation) magnitude. We will discuss the interest and application of effect size in metabolomics and we will present the highlighted candidate biomarkers in terms of discrimination potential.

P-56

An untargeted lipidomic analysis reveals ganglioside GM2/GM3 balance and the regulation of GM2-AP cofactor through GRP94 chaperone as important new key players in brain metastasis

PRESENTING AUTHOR: Carmen Bedia, Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Spain

CO-AUTHORS: Míriam Badia, Laia Muixí, Thierry Levade, Romà Tauler, Angels Sierra

GRP94 is an ATP-dependent chaperone able to regulate pro-oncogenic signaling pathways. Previous studies have shown a critical role of GRP94 in brain metastasis pathogenesis and progression. In this work, we explored if GRP94 regulates lipid metabolism in GRP94-deficient cell models through LC-MS and an untargeted lipidomic analysis using the ROIMCR methodology. The results showed that some lipid species were altered in GRP94-deficient cells, specially GM2 and GM3 gangliosides. GRP94-silenced cells contain lower levels of GM3 and higher levels of GM2 compared to control cells, indicating that the catalytic pathway of GM2 was affected by the low enzymatic activity of β-Hexosaminidase (HexA), responsible for the hydrolysis of GM2 to GM3. Moreover, a deficiency of the GM2-activator protein (GM2-AP), the cofactor of HexA, is observed without any gene expression change, indicating a post-transcriptional alteration of GM2-AP in the GRP94-ablated cells. These results suggest that GM2-AP may be a client of GRP94 chaperone, resulting in defective GM2 catabolic processing and lysosomal accumulation of GM2 in GRP94-ablated cells. Overall, given the role of gangliosides in cell surface dynamics and signaling, their imbalance might be linked to modifications of cell behaviour acquired in brain metastasis progression. On the other hand, this work indicates that GM2-AP is a key factor in the maintenance of ganglioside balance in cell membranes, which is regulated by GRP94 expression. These findings highlight the relevance of GM3 and GM2 gangliosides in BrM and reveal GM2-AP as a promising diagnosis and therapeutic target in BrM research.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

BIOMEDICAL

P-57 HR-MAS NMR based metabolic profiling in thymus cancer

PRESENTING AUTHOR: Mikheil Gogiashvili, Leibniz Institut für Analytische Wissenschaften - ISAS - e.V., Germany

CO-AUTHORS: Mohammad Al Wahsh, Jörg Lambert, Roland Hergenröder, Djeda Belharrazem, Alexander Marx

The thymus is an important lymphoid organ that is directly linked to the immune system. Thymus cancer, classified either as thymoma or thymic carcinoma, shows an increasing incidence with age and is so far lacking any curative options except surgery. It is often accompanied by autoimmune diseases, anemia or a lack of antibodies. The molecular pathogenesis of thymic epithelial tumors is hardly understood especially with respect to metastasis formation and tumor recurrence. A more thorough understanding of the molecular processes in thymic tumor tissue would improve the prognosis and would offer new treatment options for thymus cancer. High resolution (HR) magic angle spinning (MAS) nuclear magnetic resonance (NMR) based metabolic profiling is increasingly being used in cancer tissue analysis, for instance to assess the correlation of the metabolic profile with prognostic factors and with clinically relevant endpoints such as survival outcome and therapy response. Since HR MAS measurements are non-destructive, metabolomics studies can be easily combined with further investigations like subsequent histological or other "omics" related analysis, for example to discover molecular subgroups of diseases by combining quantitative metabolic and transcriptomic data. Thymomas and thymic carcinomas are rare tumors (occurrence approx. 1-2 in 500 000). In this study, we for the first time performed non-targeted metabolic profiling on a very valuable cohort of 21 tissue samples of thymus tissue as well as benign and malignant thymomas by means of HR-MAS NMR. The metabolite levels are correlated with clinicopathological parameters like gender, age, histology and Masaoka classification.

P-58 Comparison of plasma metabolite profiles between healthy cohort and cancer patients in Japanese individuals

PRESENTING AUTHOR: Eiji Hishinuma, Advanced Research Center for Innovations in Next-Generation Medicine, Japan

CO-AUTHORS: Naomi Matsukawa, Daisuke Saigusa, Bin Li, Keigo Komine, Hidekazu Shirota, Muneaki Shimada, Seizo Koshiba, Masayuki Yamamoto

Altered cell metabolism, a characteristic feature for many kinds of cancers, results in changes to intracellular and extracellular metabolite concentrations. Although many kinds of metabolites were reported as biomarkers, cancer-related change of metabolism is still not well understood. In order to diagnose and treat cancer patients comprehensively and effectively, it is important to identify specific biomarkers by reliable quantification of metabolites. Our aim is to identify the changes of metabolic profiles in plasma of individuals with cancer in comparison with healthy controls by quantification of many kinds of metabolites. As a first step, plasma concentrations of metabolites including amino acids, biogenic amines, acylcarnitines, glycerophospholipids, sphingolipids, and hexoses were quantified using LC-MS/MS and FIA-MS/MS (AbsolutelIDQ p180 kit). We compared metabolic profiles of plasma samples from cancer patients (gastric, ovarian, colorectal, pancreatic cancer, etc.) with those from healthy controls. As a result of principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA), cancer patients showed different metabolic profiles compared to healthy controls. Plasma concentrations of some amino acids, biogenic amines, and glycerophospholipids were significantly changed in the case of cancer plasma. Especially, tryptophan, histidine, and lysophosphatidylcholines were decreased, while glutamine was increased. These metabolites may be involved in the progression of cancer. Our data suggest that exhaustive profiling of plasma metabolites contributes to personalized medicine for cancer.

P-59 Spatial Information of Metabolites Using Mass Spectrometry Imaging on Breast Needle Biopsy

PRESENTING AUTHOR: Vincen Wu, Imperial College London, United Kingdom

CO-AUTHORS: Paolo Inglese, Hui-Yu Ho, Andreas Dannhorn, Emine Kazanc, Goncalo Correia, James McKenzie, Stephanie Ling, Evdoxia Karali, Nikolaos Koundouros, Hiromi Kudo, Peter Kreuzaler, Sami Shousha, Ian Gilmore, Mariia Yuneva, Richard Goodwin, Josephine Bunch, George Poulogiannis, Zoltan Takats

Breast cancer is one of the most prevalent forms of cancer in women worldwide, and it is a highly heterogeneous and complex disease with distinct molecular features. The gold standard for clinical diagnosis of breast cancer is through histopathology and the presence or absence of certain marker proteins. These methods do, however, not fully capture the biological heterogeneity of the disease. Mass spectrometry imaging is a powerful tool that allows us to produce metabolic images of clinical tissues with their corresponding distribution and intensity. For this study, 12 breast needle biopsies were analyzed and compared using multivariate analysis, towards the profiling of altered metabolites and lipids between different tissue types, to understand the heterogeneity of breast cancer.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

BIOMEDICAL

P-60 Multiplatform metabolomics for the biomarker discovery in pancreatic cancer

PRESENTING AUTHOR: Raquel Cumeras, Universitat Rovira i Virgili (URV), Spain

CO-AUTHORS: Raquel Cumeras, Esther Molina-Montes, Alfredo Carrato, Xavier Molero, Francisco X. Real, Núria Malats, Xavier Correig

Pancreatic ductal adenocarcinoma (PDAC) or pancreatic cancer, is the deadliest cancer worldwide, despite its relatively low population incidence, and early-stages biomarkers are needed. Samples were selected from a large case-control study (4000-subjects) on pancreatic cancer (PanGenEU) conducted in 28-centres from 6-European countries. In this study, metabolomics profiles of 60 PDAC cases and 60 controls from 2-centres in Spain, were evaluated using non-targeted metabolomics with UHPLC-QTOF-MS, GC-QTOF-MS for serum samples (polar and non-polar phases), and 1H-NMR for urine and fecal samples. LC-MS peak peaking, alignment and retention drift correction was done with XCMS, then QC-normalized with PQN. Samples from both centers were analyzed together, randomizing their order in the experimental analysis, so the relevant metabolites identified (FDR<0.05) were not influenced by an experimental batch. The univariate t-test returned 484 relevant features. The features whose m/z returned a hit either in METLIN or HMDB were selected for MS/MS. For GC-MS, data was deconvoluted and aligned with eRah package in R and metabolites were ID with Golm Database. In NMR, to account for the potential dilution effect of urine, metabolites were PQN-normalized and used the kNN-imputation (k=5). Within the multiplatform analysis, the following metabolites were found up-regulated in PDAC samples: 1-methylnicotinamide; various secondary bile acids (such as glycocholic acid, and taurocholic acid); and some sugars (like galactose). With this multiplatform and multifluid results, and relevant clinical and biochemical metadata we will generate a predictive model for PDAC. Model results combining the serum, urine and fecal relevant features would be presented at the conference.

P-61 Metabolome analysis of cancer-derived extracellular vesicles under different oxygen concentration

PRESENTING AUTHOR: Akiyoshi Hirayama, Keio University, Japan

CO-AUTHORS: Ryosuke Hayasaka, Masaru Tomita, Tomoyoshi Soga

Extracellular Vesicles (EVs) are facilitators of cell-to-cell communication. Cancer-derived EVs contribute to cancer progressions such as distant metastasis, angiogenesis, and immunosuppression. EVs contain functional cellular components including DNA, mRNA, microRNA, and protein. However, metabolomic profiling in cancer-derived EVs remains largely unexplored. The purpose of this study is to explain comprehensive metabolomic profiling of pancreatic cancer-derived EVs. As a model for studying cancer metabolism, we evaluate the difference between metabolomic profiles in EVs obtained from cancer cells cultured in normoxic or hypoxic conditions. Pancreatic cancer cell line Panc1 was cultivated under normoxic (20% oxygen) and hypoxic (1% oxygen) conditions. Cells were sampled using methanol and EVs were isolated from conditioned medium using ultracentrifugation. The amount of EVs was determined by nanoparticle tracking analysis and the protein level of the CD9 exosomal marker was measured using enzyme-linked immunosorbent assay (ELISA). Metabolome analysis was performed by using capillary ion chromatography-mass spectrometry and liquid chromatography-mass spectrometry. We identified more than 180 kinds of metabolites in pancreatic cancer-derived EVs. In addition, principal component analysis (PCA) of metabolites in EVs showed some separation between normoxia and hypoxia. These results suggest that the metabolomic profiling of cancer-derived EVs differ different oxygen concentrations.

P-62 The metabolic footprint of intensive weight management in an open-label, cluster-randomised trial (DIRECT)

PRESENTING AUTHOR: Caroline Bull, University of Bristol, United Kingdom

CO-AUTHORS: Laura J. Corbin, Michael E. J. Lean, Roy Taylor, Naveed Sattar, Nicholas J Timpson

Type 2 diabetes is strongly related to weight gain and accumulation of excess fat within the liver and pancreas. Results from the Diabetes Remission Clinical Trial (DIRECT) have shown that a professionally supported intensive weight management programme can enable patients to undergo diabetes remission. In this trial of 298 patients, 46% of those in the intervention arm (68/149) achieved remission at 12 months. Whilst the measurement of standard clinical indicators suggests improved metabolic health in the intervention group, in this work we present a full evaluation of the metabolic consequences of the intervention. Serum samples collected from patients at baseline and one-year have undergone analysis by mass spectrometry (UPLC-MS/MS) and nuclear magnetic resonance (NMR) spectroscopy. In a preliminary analysis of 273 samples, we used a mixed linear modelling approach to compare the levels of 933 MS-derived metabolites in the intervention group (n=125) versus the control group (n=148) at one-year post-intervention. We have shown >350 metabolites to be associated with the intervention including branched chain amino acids (e.g. alpha-hydroxyisovalerate), carbohydrates (e.g. mannose) and lipids, such as sphingomyelins. Integration of our results into a metabolite-disease interaction network indicate potential relevance for cancer and neurological phenotypes. Whilst many of the changes we see are likely due to the intervention effect on weight which was estimated to be -8.8kg (95% CI: -10.3, -7.3), there is also some indication that the metabolite profile reflects dietary and lifestyle changes. These experimental study data on diabetes remission augment the understanding gained from observational studies of diabetes development.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

BIOMEDICAL

P-63

Targeted Multi-OMICS: Rapid plasma profiling of a bladder and lung cancer human cohort

PRESENTING AUTHOR: Billy Molloy, Waters Corporation, United Kingdom

CO-AUTHORS: Sarah Lennon, Lee Gethings, Robert Plumb

Cancer is a complex, life threatening disease, existing in many forms. Here, we present a study comparing plasma samples from cohorts of bladder and lung cancer patients, with healthy controls using a high-throughput targeted OMICS workflow. This workflow allows for rapid screening of various compound classes using a single LC-MS platform. A known level of a labelled analogue from each compound class was added to each sample. The level of each analyte was then estimated using its ratio to this. Data was collected for 18 samples (6 controls; 6 bladder cancer; 6 lung cancers). QC's (a pool from all samples) were acquired every ninth injection. In total, 206 injections were performed (runtime = 22hr). 128 compounds were measured, generating a %CV <20% for the QC samples: 80 proteins, 20 acylcarnitines and 28 amino acids. Valine-d8 (amino acid spiked in samples) is used as an example to illustrate the consistency of response across the whole study (CV= <5%). Pair-wise comparisons using a t-test were performed on each compound class. The amino acid sarcosine was demonstrated to be up-regulated in both lung and bladder cancer samples; the acyl carnitine Octenoyl-carnitine (C8:1) was down-regulated in bladder cancer subjects; and protein analysis highlighted various differentiating species, including Apolipoproteins. This data demonstrates the ability of this targeted approach to highlight potential markers in a high-throughput manner. Method development was unnecessary, and results were obtained in <24 hours. The next step would be to validate the markers by performing a more statistically rigorous study.

P-64

Rational Metabolic Engineering – Metabolism Driven Strategy for Optimization of Cancer Treatment.

PRESENTING AUTHOR: Anna Halama, WCMQ, Qatar

CO-AUTHORS: Shaima Dib, Iman Achkar, Sara Kader, Michal Kulinski, Gabi Kastenmueller, Olivier Elemento, Steven S. Gross, and Karsten Suhre.

The metabolic processes of a cancer cell in comparison with a normal cell are strongly deregulated, and could be associated with increased energetic and adaptive needs required for proliferation, progression and metastasis in challenging microenvironment. Therefore, altered cancer metabolism become an attractive target for therapeutic intervention. For instance, glutaminase inhibitors, same as fatty acid synthesis inhibitors, have shown efficacy in preclinical testing and entered already clinical trials. However, given the complexity of metabolic interactions it could be hypothesized that inhibition of one metabolic pathway might trigger series of metabolic adaptations towards cancer cell survival and as a result end up with a treatment failure. Here, we are proposing to monitor metabolic landscape of cancer cell at its baseline as well as under treatment to provide further insight into cancer metabolic plasticity, which might lead to prediction of rational intervention in the cancer metabolism and thus treatment optimization. We have determined metabolic baseline of 6 normal and 30 cancer cell lines from lung and breast using non-targeted metabolic profiling. We identified 380 metabolites out of which 130 molecules, from various metabolic classes, showed significant deregulations across the cancer cell lines in comparison to normal cells. We further draw a map of cancer cell metabolism and determined key metabolic deregulations. Here, we report on metabolic plasticity under glutaminolysis inhibition and characterize strategies for treatment optimization driven by metabolic analysis. With this study we are proposing approach for optimization of cancer treatment strategies based on metabolic responses, which we call Rational Metabolic Engineering.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

BIOMEDICAL

P-65

Quantitative analysis of 2-hydroxyglutarate in malignant gliomas

**PRESENTING AUTHOR:** Peter Bystrický, Jessenius Faculty of Medicine in Martin Comenius University, Slovakia(Slovak Republic)

**CO-AUTHORS:** Simona Holubčíková, Ivana Kašubová, Romana Richterová, Branislav Kolarovszki, Zora Lasabová, Peter Račay

Concentrations of D- and L- 2-hydroxyglutarate (2-HG) were determined in tumor tissue samples of glioma patients WHO grade I – III (astrocytoma, oligodendroglioma, secondary glioblastoma) with possibility of genetic mutation on isocitrate dehydrogenase (IDH) 1 or 2 in vitro. The concentrations were determined (quantified) by HPLC-HRMS technique using Agilent HPLC and Bruker Q-TOF HRMS spectrometer setup. The D-2-HG concentration was double checked by D-2-Hydroxyglutarate Colorimetric Assay Kit. Concurrently the genetic mutation analyses of both IDH 1 and 2 were performed by isolation of cancer tissue DNA, PCR amplification and subsequent Sanger sequencing. This was to confirm the correlation of 2-HG in vitro concentrations in tumor tissue and the results from mutation analyses. Also the in vitro HPLC-HRMS data were correlated with immunohistological findings.

P-66

Metabolomic profiles throughout the continuum of colorectal carcinogenesis: a targeted metabolomics approach

**PRESENTING AUTHOR:** Stefanie Brezina, Institute of Cancer Research, Medical University of Vienna, Austria

**CO-AUTHORS:** Stefanie Brezina, Andreas Baierl, Anne J.M.R. Geijsen, Eline van Roekel, Pekka Keski-Rahkonen, David Achaintre, Martijn Bours, Fränzel J.B. van Duijnhoven, Biljana Gigic, Tanja Gumpenberger, Andreana N. Holowatyj, Dieuwertje E.G. Kok, Annaleen Koole, Arve Ulvik, Nivonirina Robinot, Jennifer Ose, Alexis B. Ulrich, Per Magne Ueland, Ellen Kampman, Matty Weijenberg, Nina Habermann, Augustin Scalbert Cornelia M. Ulrich, Andrea Gsur

**BACKGROUND.** Colorectal cancer is a major public health concern worldwide, remaining the third leading cause of cancer-associated mortality. Colorectal cancer has a natural history of evolution from normal mucosa to adenoma to cancer, thereby providing a window of opportunity for effective intervention and prevention. Thus, the discovery of biomarkers that aid in the characterization of risk of progression along the colorectal carcinogenesis are urgently needed to tailor prevention strategies. **METHODS.** Targeted metabolomics analysis was performed on plasma samples from 831 newly diagnosed colorectal cancer patients, 600 adenoma patients, and 753 controls, using mass spectrometry and the Biocrates AbsoluteIDQ p180 Kit. Samples included in this study were derived from five colorectal cancer cohorts embedded in the European MetaboCCC consortium. We applied a comprehensive data analysis strategy to investigate signals of changes in the metabolomic profile that vary along the continuum of colorectal carcinogenesis. **RESULTS.** Data on 131 metabolites were applicable for further analysis in all study samples. We established a categorical regression model to identify metabolites associated with the development of colorectal cancer. Metabolites significantly associated with colorectal carcinogenesis were further used to establish a random effects model able to predict colorectal cancer patients, adenoma cases and controls. **CONCLUSION.** The complementary study population, brought together as part of the MetaboCCC consortium, provided a unique resource for comprehensive investigations enabling a distinction of malignancy potential. Our findings suggest that metabolites associated with the risk for colorectal carcinogenesis can be used in future for risk stratification, e.g., for tailored screening strategies by endoscopy.
<figure><img src="image_36.png" /></figure>

**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

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BIOMEDICAL

P-67

Spatial differentiation of metabolism in prostate cancer tissue detected with mass spectrometry imaging

**PRESENTING AUTHOR:** Maria K. Andersen, Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Norway

**CO-AUTHORS:** Therese Stork Høiem, Benjamin Balluff, Marta Martin-Lorenzo, Elin Richardsen, Britt Claes, Helena Bertilsson, Ron Heeren, Morten B. Rye, Guro F. Giskeødegård, Tone F. Bathen, May-Britt Tessem

Molecular profiling of prostate cancer tissue is challenging due to the heterogeneous tissue composition. Mass spectrometry imaging (MSI) enables identification of spatial distribution of biological molecules on tissue sections. In this study, we performed metabolic profiling of 45 prostate cancer tissue samples using matrix assisted laser desorption/ionization time-of-flight (MALDI-TOF) MSI (negative and positive ion mode, 30 µm resolution). By pairwise comparing spectra from different tissue types (benign epithelium (BE), cancer epithelium and stroma) with multivariate orthogonalized partial least squares discrimination analysis (OPLS-DA) modeling, we identified several differences in metabolism. The antioxidant-related metabolites taurine and oxidized glutathione had higher levels in stroma compared to benign epithelium. Citrate and spermine had reduced levels in stroma and in cancer epithelium compared to BE, which confirms previous findings. Lastly, carnitine and acetyl carnitine, which are parts of the carnitine shuttle, had higher levels in cancer epithelium compared to BE, while no differences were observed between stroma and BE. The carnitine shuttle is important for the regulation of β-oxidation of lipids vs. lipid synthesis balance. Mass identity of the metabolites was verified through MS/MS. In conclusion, we identified alterations in key molecular processes, such as lipid β-oxidation, prostatic secretory function and inflammation, in prostate tumor tissue using MALDI-TOF MSI. The significant differences in metabolite distributions between the defined tissue structures, pinpoint the importance of access to methodology capable of providing spatial information.

P-68

Comparison of tissue sample preparation methods for comprehensive LC-MS metabolomic analysis of gastrointestinal stromal tumour

**PRESENTING AUTHOR:** Szymon Macioszek, Medical University of Gdansk, Poland

**CO-AUTHORS:** Urszula Kijanko, Michał Jan Markuszewski

Gastrointestinal stromal tumour (GIST) is a rare type of cancer that affects around 15 people per million in Europe. Most often GIST develops as a consequence of mutations in KIT gene or PDGFRA gene, less frequently. However, metabolic patterns during GIST development have not yet been investigated and elucidated. To acquire knowledge about changes in biochemical pathways in the cancer tissue, we chose to apply untargeted metabolomics with the use of LC-MS. The first stage of the study was focused on selecting the most appropriate sample preparation method. Due to limited availability of GIST tissue samples, we aimed at developing a method that provides possibility of extracting both polar and lipophilic metabolites from one small GIST specimen. Tissue samples were homogenized with a 50:50 mixture (v/v) of methanol and water in ratio 1:10 (w/v) and obtained homogenate was subjected to five different methods of extraction. They included monophasic extraction with methyl tert-butyl ether (MTBE) and methanol, biphasic extraction with different ratios of MTBE, methanol and water as well as with dichloromethane, methanol and water, and two-step extraction with the same solvents. Organic extracts were analyzed with reversed phase LC-TOF-MS, while HILIC separation was used for polar extracts. Criteria for sample preparation method selection were based on the number of features detected in the extracts and reproducibility of extraction procedure. The selected method will be further used in metabolomic fingerprinting of GIST tissue specimens, which can complement genomic studies on GIST or propose potential new therapeutic targets.

P-69

Method development for determination of modified nucleosides and deoxynucleosides in urine and plasma samples

**PRESENTING AUTHOR:** Magorzata Patejko, Medical University of Gdańsk, Poland

**CO-AUTHORS:** Wiktoria Struck-Lewicka, Danuta Siluk, Marcin Markuszewski,

Modified nucleosides and deoxynucleosides are products of RNA and DNA turnover. They are not metabolized and cannot be utilized for synthesis of RNA and DNA molecules. They are excreted in unchanged form. Consequently, a correlation between their elevated level in urine and pathophysiological disorders development can be expected. Increased level of modified nucleosides and deoxynucleosides was observed in such diseases as: hepatocellular carcinoma, breast cancer or urogenital cancer. The aim of the study is the targeted metabolomics analysis of 11 modified nucleosides and deoxynucleosides in urine and plasma samples collected from bladder cancer patients with the use of LC-QqQ/MS technique. Since proper sample treatment influences obtained results significantly, the first task of the research covered the development of sample preparation procedure. This included optimization of separation conditions and solid-phase extraction procedure (SPE). Different chromatographic conditions were compared, including: type of stationary phase, flow rate, column temperature and gradient programme. According to SPE, differences in the sugar moiety between nucleosides and deoxynucleosides cause differences in their extraction ability and consequently difficulties with sorbent selection that allows for the extraction of nucleosides and deoxynucleosides at once. Previously, nucleosides and deoxynucleosides were more often analyzed separately. The goal was to develop method for simultaneous extraction of nucleosides and deoxynucleosides from urine and plasma. Different sorbents were evaluated by their selectivity, recovery and ability to extract modified nucleosides and deoxynucleosides. Method based on selected sorbent was further optimized. Acknowledgement: The work has been supported by the National Centre of Science, project no 2018/29/N/NZ7/02299.
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BIOMEDICAL

P-70

Application of targeted metabolic analysis to study glycolysis-related metabolic changes in oral cancer cells

PRESENTING AUTHOR: Chul-Ho Jeong, College of Pharmacy, Keimyung University, South Korea

CO-AUTHORS: Won-Jun Jang, Ji Hae Seo

The application of metabolomics to cancer research field could help to explain the causes of phenotypic changes during acquisition of drug resistance and metabolic alteration in cancer cells. In this reason, understanding metabolic change induced by altered glycolytic pathway in cancer cells is crucial for overcoming drug resistance in various cancers. In the present study, the mass spectrometry-based targeted metabolic profiling was performed to compare the metabolic changes in oral cancer cells, SCC15 following treatment with 2-deoxy-D-glucose (2-DG), 2-DG+pyruvate, and 2DG+mannose. Then we quantified and compared statistically five metabolite groups, acylcarnitines, amino acids and biogenic amines, glycerophospholipids, sphingolipids and monosaccharides. Our targeted metabolomic analyses revealed that significant changes were evident in metabolic pathways involved in the regulation of amino acids (15), polyamine (1), and fatty acids (3). Significant decreases in the levels of amino acids, polyamine and significant increases in the levels of the lysophosphatidylcholine, phosphatidylcholine and sphingomyelin were observed in 2DG-treated SCC15 cells. Furthermore, we found that treatment with pyruvate or mannose significantly restored metabolic changes in 2DG-treated SCC15 cells. Collectively, this study reveals that there are increased metabolic demands reflecting the changes in glycolysis-related amino acids metabolism, which might advance our understanding of metabolic alteration in cancer.

P-71

Metabolic correlations to weight change in patients with head- and neck cancer: A pilot study

PRESENTING AUTHOR: Kristian Pirttilä, Uppsala University, Sweden

CO-AUTHORS: Ylva Tiblom Ehrsson, Göran Laurell, Mikael Hedeland, Torbjörn Arvidsson, Curt Pettersson

Patients afflicted with head and neck cancer (HNC) often suffer from unintentional weight loss and cancer cachexia is prevalent. This pilot study is a part of a multi-center study of HNC patients in Sweden. The aim was to investigate the correlation of the plasma metabolome at different time points to the weight change of patients. Plasma samples from 31 patients taken at three different time points (at diagnosis, 7 weeks after treatment started, and 12 weeks after treatment ended) were analyzed using a HILIC-UHPLC-Q-TOF-MS-protocol. The treatment modality of patients varied, however 27 out of the 31 patients had received radio therapy. The metabolome at the different time points as well as changes between time points were correlated using orthogonal projection to latent structures (OPLS) to a weight outcome factor calculated for each patient based on clinical measurements. A correlation with weight outcome was found in the 7 week (R2 0.807, Q2 0.412, p = 0.07) and 12 week follow-up samples (R2 0.679, Q2 0.361, p < 0.01) and also in the fold changes from the baseline to the 7 week follow-up (R2 0.722, Q2 0.387, p < 0.05). In total 111 metabolites were selected from the models. Among the metabolites with correlation were a number of lysophosphatidylethanolamines (LysoPE) and lysophosphatidylcholines (LysoPC) along with a number of short-chain acyl carnitines. These partial results may suggest downregulation of lipogenesis in the liver in correlation to weight loss, warranting further research.

P-72

Discovery of sex differences in colon cancer metabolism

PRESENTING AUTHOR: Yuping Cai, Yale University, United States

CO-AUTHORS: Yuping Cai, Nicholas Rattray, Yawei Zhang, Sajid Khan, Caroline H. Johnson

Colorectal cancer (CRC) is one of the most common and lethal cancers around the world. While women have a lower incidence of CRC than men they have a higher likelihood of primary tumor presentation on the right-side of colon. This is of concern as epidemiologic studies have shown that patients with right-sided colon cancer (RCC) have poorer clinical outcomes than those with left-sided colon cancers (LCC). However, the reasons for this difference in outcome are not known. Aberrant metabolism is a significant biological feature of CRC; and gene expression patterns have shown that some cancers can be categorized into a "metabolic subtype" of which the abundance is skewed towards RCCs. To unravel sex differences in metabolism for CRC patients, we performed untargeted profiling on colon tissues (normal and tumors; n=271) with stratification by sex and primary tumor location. Our preliminary data shows that metabolites are significantly altered in both women and men with CRC, and are enriched in the following pathways: glycolysis, amino acid metabolism, methionine metabolism, and nucleotide metabolism. Widespread sex-specific differences in metabolites were seen and included tryptophan, citrulline, lactate, N1, N12-diacetylspermine, fatty acids, and fatty acyl carnitines. Of note, when comparing women and men with RCC, women had elevated fatty acid metabolism and transportation, whereas in men, fatty acid utilization was not elevated and instead aerobic glycolysis was upregulated. These results indicate that sex-specific differences exist in tumor substrate utilization for energy and cell growth.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday – all odd number posters will be on display.**

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday – all even number posters will be on display.**

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P-73 Metabolomics in rat models of hypertension

PRESENTING AUTHOR: Dorian Maroil, UMONS, Belgium

Hypertension is a complex and multi-factorial disease and its chronical form affects more than one billion people worldwide. Hypertension may become very critical as it is a major risk factor for cardiovascular morbidity and mortality. Most of hypertension cases are not a consequence of another disease but due to genetic, lifestyle or environmental factors Sometimes, it may also develop after renal failure. Metabolomics is a powerful tool to evaluate global metabolic perturbations in relation with disease, toxicity or treatments. It has proved very helpful for the follow up and identification of early potential biomarkers of these conditions. In order to identify underlying mechanisms involved in the onset of hypertension, we compared the metabolomics signature of either spontaneous or chemically-induced rat models of hypertension. Hypertension was induced in rats by oral administration of NO synthase inhibitor, L-NAME, through the drinking water for 4 weeks. This treatment not only increased the blood pressure but also reduced the renal function. The second model was based on Spontaneously hypertensive (SHR) rats which developed hypertension at the age of 6 weeks. The comparison of metabonomic signatures obtained by proton NMR spectroscopy of urine and serum samples collected from both rat models highlighted some common metabolic patterns which could be further developed as potential biomarkers of this pathology.

P-75 Statins and antiplatelet treatment after acute myocardial infarction in patients with acute myocardial infarction: HILIC-MS targeted metabolomics of the BATTLE-AMI study

PRESENTING AUTHOR: Carolina Raíssa Costa Picossi, Fundacion San Pablo CEU, Spain

CO-AUTHORS: Carolina Raíssa Costa Picossi, Ana Paula de Godoy Fernandes, Jorge Sáiz, Andréa Tedesco Faccio, Marina Franco Maggi Tavares, Coral Barbas, Francisco Javier Rupérez

Acute myocardial infarction (AMI) is the largest cause of mortality in the world. The 2017 ESC Guidelines for the management of AMI recommend the administration of an antiplatelet besides the conventional statin therapy although the metabolic consequences of such simultaneous use are not yet fully explored. The objective of this work was to evaluate by a targeted metabolomics approach, part of the metabolic mechanisms involved in 4 combinations of treatments after cardiac ischemia, as part of a comprehensive study within the BATTLE-AMI clinical trial (NCT02428374). Plasma samples were collected from 369 patients who suffered AMI with ST-segment elevation, one day and six months after AMI. All patients received one combined treatment with one antiplatelet (Clopidogrel or Ticagrelor) plus one statin (Simvastatin or Rosuvastatin). After a judicious method development, samples were analyzed by HILIC-MS in positive mode. HILIC provided high separation efficiency of polar analytes. Besides mobile phase and gradient optimization, method development included matrix effect study and data acquisition parameters for Dynamic MRM optimization for 38 compounds including acylcarnitines, amino acids and related compounds. All compounds were quantified, and compared by means of repeated measures ANOVA. Overall, all treatments were equivalent, and significant differences could be seen in less than 25% of the measured compounds, associated either to the combination or the efficiency of the treatment. Lysine metabolism (catabolism and methylation) upraises as the most affected process in these patients. The consequences of such differences will be evaluated in the context of the whole trial.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

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BIOMEDICAL

P-77

Estimation of Metabolomic Networks with Gaussian Graphical Models

PRESENTING AUTHOR: Katherine Shutta, University of Massachusetts Amherst, United States

CO-AUTHORS: Subhajit Naskar, Kathryn M. Rexrode, Denise M. Scholtens, Raji Balasubramanian

Network-based metabolomic analyses have high potential to capture signatures of complex biological processes. Topological network properties such as structure, sparsity, and degree distribution provide a systems-based perspective. Unsupervised network-based approaches can provide insights into functional pathways that traditional methods have not elucidated. Estimated networks can provide reinforcement for, or rationale to challenge, previously discovered pathways. The mapping of metabolites to biological pathways is incomplete; network-based approaches may foster advances in the field. Gaussian graphical model (GGM) estimation is one such approach. Modeling metabolomic data with a GGM enables biologically meaningful interpretation of the estimated edge set as a map of functional dependence between metabolites, conditioned on biological state. GGM estimation for high-dimensional datasets is an active area of research. Recently, several open-source R packages have been developed for this purpose. GGM estimation involves several choices with regard to scoring criteria, precision matrix estimation algorithms, and data transformations. For a fixed experimental setting, the different estimation methods generated by these options may result in substantially different GGM estimates. Similarly, the effectiveness of an estimation method at identifying the true network may be highly dependent on experimental factors such as sample size, number of metabolites measured, and network topology. We present results from in-depth simulations designed to characterize these variations, with the goal of providing practical guidance to researchers applying GGM approaches to metabolomics data. We consider various sample sizes, sparsities, and topologies. Application of these approaches is illustrated using data from a cardiovascular disease metabolomics study nested within the CATHGEN repository.

P-78 Untargeted Multiplatform Metabolomics in the quest for biomarkers of cardiac alterations in patients with Cri Du Chat Syndrome

PRESENTING AUTHOR: Danielle Zildeana Sousa Furtado, Fundación CEU San Pablo, Spain

CO-AUTHORS: Fernando Brunale Vilela de Moura Leite, Nilson Antonio Assunção, Coral Barbas, Francisco Javier Rupérez,

Cri Du Chat Syndrome (CdCS) is a rare genetic syndrome resulting from a partial deletion of the short arm of chromosome 5, which affects an estimated 1 in 50000 live births. Congenital cardiac anomalies in CdCS patients are present in 15 to 20% of the patients. This complication worsens patients' prospect. Detection of specific biomarkers within CdCS patients will help to understand the relationship between cardiac problems and CdCS. Moreover, new diagnostic biomarkers will help in early detection and management of cardiac alterations. Untargeted multiplatform metabolomics (GC/MS, CE/MS and LC/MS – lipidomics) was applied to plasma samples from CdCS patients with (n=13) and without (n=13) cardiopathy. Ion grouping (Molecular Feature Extraction), deconvolution, and multialignment provided the matrices for statistical analysis. Afterwards, multivariate analysis (Principal Components Analysis, Hierarchical Clustering), as well as univariate analysis were performed. 44 statistically significant compounds, differentiating between cardiopathy and control groups were annotated. Level 2 and 3 annotation (MSI) could be achieved by means of different strategies, including CEU Mass Mediator (REF) for simultaneous query in online databases. 25 metabolites increased and 19 decreased in cardiopathy patients. Results suggested dysfunction in fatty acid and phospholipid metabolism, as well as in amino acids and short chain organic acids. Furthermore, a multivariate ROC Curve (AUC=0.974) based on Linear Support Vector Machine showed that 34 metabolites could be used combined as potential biomarkers to diagnose cardiopathy in CdCS patients. The interpretation of these results provides further insight in understanding cardiac diseases in Cri du Chat Syndrome.
<figure><img src="image_37.png" /></figure>

**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

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P-79

Metabolomics Studies Identify Sugar Alcohols as Predictors of Incident Cardiovascular Disease Risks

**PRESENTING AUTHOR:** Hassan Alamri, Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, KSAU-HS, Riyadh, Saudi Arabia

**CO-AUTHORS:** Hassan Alamri, Ina Nemet, Nisreen Nimer, Tomas Cajka, Oliver Fiehn, Wilson Tang, Valentin Gogonea, Stanley L. Hazen

Identification of novel metabolites for early identification of individuals at risk for future cardiovascular events is critical to provide new ways to both diagnose disease states and reveal previously unsuspected pathways associated with cardiovascular disease (CVD) and its pathogenesis. We performed untargeted metabolomics studies employing high resolution gas chromatography mass spectrometry on >12 h fasting plasmas from sequential consenting subjects (n=1162) undergoing elective diagnostic cardiac evaluations with longitudinal follow-up and adjudicated incident (3 year) adverse event monitoring. Among the identified metabolites, several sugar alcohols were significantly associated with incident CVD event risk. To validate the semi-quantitative untargeted metabolomics findings, an independent and new stable-isotope dilution liquid chromatography tandem mass spectrometry method (LC-MS/MS) for the quantitation of sugar alcohols was developed and validated. The method includes plasma protein precipitation and sugar alcohols derivatization with acetic anhydride, followed by liquid-liquid extraction and LC/MS/MS analysis. Preliminary analysis on small and independent validation cohort of subjects (n=200) undergoing cardiac risk factor evaluation/modification in a preventive cardiology clinic replicated the observed CVD risks associated with select sugar alcohols. A complete validation analysis of the targeted sugar alcohols as predictors of incident CVD risks (myocardial infarction, stroke or death) in a large and non-overlapping cohort of patients (n > 2000) also confirmed the potential clinical utility of sugar alcohols as predictors of incident CVD risks. Mechanistic animal model studies to explore whether associations observed between select sugar alcohols confirmed and CVD phenotypes are causally linked are under way.

P-80

Untargeted NMR Metabolomics of Adrenal Hypertension

**PRESENTING AUTHOR:** Nikolaos G Bliziotis, RadboudUMC, Netherlands

**CO-AUTHORS:** Jaap Deinum, Graeme Eisenhofer, Maria-Christina Zennaro, Paolo Mulatero, Alek Prejbisz, Felix Beuschlein, Martin Fassnacht, Livia Lenzini, Michael Conall Dennedy, Marco Boscaro, Filippo Ceccato, Gian Paolo Rossi, JM Connell, Tracy Williams, Michel Azizi, Laurence Amar, Jérôme Bertherat, Anne-Paule Gimenez Roqueplo, Casper K Larsen, Eleanor Davies, Udo FH Engelke, Ron A Wevers, Leo AJ Kluijtmans, Henri JLM Timmers

**Background:** The ENSAT-HT project aims to establish a biomarker signature for different forms of adrenal hypertension (AHT) based on a multi-omics approach, including untargeted plasma metabobolomics. Our aim is to define the metabolic signature of AHT patients suffering from either Primary Aldosteronism (PA, n=106), Cushing's Syndrome (CS, n=39) or Pheochromocytoma and Paraganglioma (PPGL, n=98), and compare it to primary hypertensives (PHT, n=109) and healthy volunteers (HV, n=133). Methods: Heparinized plasma samples were collected from all study subjects and analyzed in a randomized order, along with Quality Controls (QC), using proton Nuclear Magnetic Resonance spectroscopy (1H-NMR). The resulting spectra were processed and converted to a readable table by multivariate statistical analysis (MVA) tools; Principal Component Analysis (PCA) was applied to check for outliers and trends within the dataset and Partial Least Squares Discriminant Analysis (PLS-DA) to build a sample classification model. Results: Upon inspection of the PCA score plot of NMR plasma data, a tight clustering of the QC samples was observed, indicating the analytical robustness of the complete methodological approach. A PLS-DA model was built for classification of samples in either PHT or AHT with an accuracy of >80%. Conclusions: A reliable NMR metabolomics approach was applied on human plasma samples. The initial analysis suggests that patient classification based on the presence of either adrenal or primary hypertension appears to be feasible. Future plans include diminishing the effects of confounders and the application of Multilevel MVA methods to delineate the pathophysiological mechanisms of AHT.

P-81

Omics approach to study dyslipidemia

**PRESENTING AUTHOR:** eleonora quartieri, AUSL-IRCCS of Reggio Emilia, Italy

**CO-AUTHORS:** Lucia Merolle, Chiara Maraccini, Erminia di Bartolomeo, Luca Scarano, Stefania Bergamini, Roberto Baricchi, Thelma Pertinhez

Dyslipidemia, lipoprotein overproduction or deficiency, is an important risk factor for coronary heart disease and stroke. Metabolomics information about dyslipidemic patients is still limited. Patients non-responder or intolerant to statins usually undergo lipoprotein apheresis (LA) to lower LDL levels. LA exert pleiotropic effects altering a number of blood components. [1,2] We performed a multi-parametric assessment of the inflammatory, PCSK-9 level, together with metabolic and proteomic profiles of dyslipidemic patients undergoing LA to gain information about LA effects and to deeper investigate the disease. Serum samples from 9 patients undergoing three consecutive LA (B. Braun) procedures were assayed. Samples were collected before and after each procedure. Nuclear magnetic resonance and ESI-Q-ToF LC/MS were used to assess metabolomics and proteomic patterns, respectively. Lipid profile and PCSK-9 levels were biochemically measured. Together with the expected depletion of lipoprotein-related proteins and PCSK-9 levels, we observed a reduction of complement- and inflammation-related proteins after each LA procedure. We identified around 50 soluble metabolites defining the metabolic baseline profile of dyslipidemic patients (before LA treatment). LA influences patient's proteomic pattern whereas has no impact on intermediate and final products of metabolic pathways. For 3 out of the 9 patients, we identified the accumulation of branched-chain amino acids. The integration of metabolomics with other omic-based approaches turns out to be relevant to identify clinical markers to support physicians in the choice of the best treatment options.
<figure><img src="image_38.png" /></figure>

**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

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P-82

Metabolomics approach coupled with Leaman score to re-stratify coronary artery plaque burden: a translational pilot study with asymptomatic subjects of intermediate cardiovascular risk

PRESENTING AUTHOR: Aline Martins, Universidad CEU San Pablo, Spain

CO-AUTHORS: Mariana Ubaldo Barbosa Paiva, Diego Viana Neves Paiva, Henrique Louzan Machado, Leonardo Jadyr Silva Rodrigues Alves, Fabio Neves dos Santos, Marcos Nogueira Eberlin, Carolina Raíssa Costa Picossi, Guilherme Urpia Monte, Fernando Antibas Atik, Carolina Gonzalez-Riaño, Francisco J. Ruperez, Coral Barbas, Aline Maria Araújo Martins

Background: Current risk stratification strategies for coronary artery disease (CAD) have low predictive value in asymptomatic patients classified as intermediate Framingham risk. Metabolomic approach, in addition to detailed anatomical imaging by coronary computed tomography angiography (CCTA), could allow to better identify patients at risk of cardiovascular events. Purpose: To analyze the overall metabolic profile within the tomographic Leaman (CT - LeSc) terciles on the most clinically relevant scenarios - CNvsT3, T1vsT3, CNvsT1. Methods: A total of 20 asymptomatic subjects classified as intermediate CAD risk according to the Framingham score with negative test for ischemia (myocardial perfusion scintigraphy), and normal ventricular fraction (LVEF) were recruited into four groups (CN, T1, T2, T3) according to CCTA results and evaluated by UPLC-QTOF/ MS based untargeted metabolomics, correlating to patient's clinical data. CEU Mass Mediator was used to annotate the significant metabolites after univariate (t-test) and multivariate non-supervised analysis for non-parametric data. The lipidic profile was compared with several markers of CAD regarding the capacity to reclassify cardiovascular risk. Results: Within the clinical phenotypes, differential metabolites were highlighted: i) control and higher risk subjects (T3>CN): MGDG, PS (22:0); ii) higher vs lower risk subjects (T3>T1): LysoPI (22:1), DG (34:2), iii) subtle clinical phenotypes (T1>CN): SM (d44:1). Conclusion(s): Metabolomics approach may be useful in clinical practice as a powerful tool for the prediction of CAD in asymptomatic subjects. The tomography Leaman phenotypes showed discriminant metabolite findings as associated with abnormal lipid metabolism and atherosclerosis early formation, enabling a molecular possibility of complementary re-classification of vulnerable subjects.

P-83

Lipidome improves predictive ability of subclinical atherosclerosis over traditional risk factors: The Cardiovascular Risk in Young Finns Study

PRESENTING AUTHOR: Pashupati Mishra, Tampere University, Finland

CO-AUTHORS: Pashupati P. Mishra, Leo-Pekka Lyytikäinen, Binisha H. Mishra, Mika Kähönen, Olli T. Raitakari, Reijo Laaksonen, Terho Lehtimäki

Background: Early detection of atherosclerotic process is crucial for primary prevention of cardiovascular diseases. Subjects and methods: We investigated predictive ability of serum lipidome using LC-MS/MS technique for subclinical atherosclerosis assessed by carotid intima-media thickness (cIMT) in Young Finns Study cohort in 2007 (number:2009, age:30-45 years, women:55%). Statistical analysis was done with dichotomized cIMT data (cases: value >= 90th percentile vs. controls: value <90th percentile). Differential expression analysis of lipidome data between cases and controls was performed with Student's t-test. Differentially expressed lipid species were selected for prediction models. Reference predictive model with major traditional risk factors and two test predictive models; one with lipid species and traditional risk factors (test model1) and other with lipid species only (test model 2) were analyzed. Model fitting and validation was done for 1000 bootstraps of original data by: i) fitting models to training data (70% data), ii) testing the models on test data (30% data), and iii) calculate accuracy measure (ROC AUC). Results: Our results suggest that serum lipidome significantly improves prediction accuracy for subclinical atherosclerosis over traditional risk factors (reference model: AUC 0.762, 95% CI [0.698, 0.823], test model 1: AUC 0.778, 95% CI [0.715, 0.838], t-test p-value: 2.2e-16). Serum lipidome also showed independent predictive accuracy equivalent to that of traditional risk factors [test model 2: AUC 0.762, 95%CI [0.698, 0.821], t-test p-value against reference model: 0.5005]. Conclusion: This study indicates that serum lipidome may help in predicting subclinical atherosclerosis for primary prevention more effectively than traditional risk factors alone.

P-84

Fast LC-ESI-MS/MS analysis and influence of sampling conditions for gut metabolites in plasma and serum

PRESENTING AUTHOR: Tom van der Laan, Leiden University, Netherlands

CO-AUTHORS: Tom van der Laan, Tim Kloots, Marian Beekman, Alida Kindt, Anne-Charlotte Dubbelman, Amy Harms, Cornelia van Duijn, Eline Slagboom, Thomas Hankemeier

In the past few years, the gut microbiome has been shown to play an important role in various disorders including in particular cardiovascular diseases. Especially the metabolite trimethylamine-N-oxide (TMAO), which is produced by gut microbial metabolism, has repeatedly been associated with an increased risk for cardiovascular events. Here we report a fast liquid chromatography tandem mass spectrometry (LC-MS/MS) method that can analyze the five most important gut metabolites with regards to TMAO in three minutes. Fast liquid chromatography is un conventionally used in this method as an on-line cleanup step to remove the most important ion suppressors leaving the gut metabolites in a cleaned flow through fraction. We compared different bloodmatrix types to recommend best sampling practices and found citrated plasma samples generally demonstrated lower concentrations and choline concentrations were significantly higher in serum samples. We demonstrated the applicability of our method by investigating the effect of a standardized liquid meal (SLM) after overnight fasting of 25 healthy individuals on the gut metabolite levels. Volunteers with increased and decreased gut metabolite serum levels could be identified, which could have been driven by the gender of the volunteers.
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P-85 Non-targeted metabolomics approach to elucidate metabolism alteration in mice hearts with cardiac-specific Retinoid X Receptor deletion

PRESENTING AUTHOR: Francisco Rupérez, Universidad San Pablo-CEU, Spain

CO-AUTHORS: Viviane Aparecida Rodrigues Sant'Anna, Ana Paredes, Miguel Fernández-García, Mercedes Ricote, Coral Barbas

The nuclear receptor Retinoid X Receptor (RXRs) is a family of ligand-dependent transcription factors that play essential role in heart development. Whereas the systemic RXRα deletion causes embryonic lethality due to cardiac defects, the functional contribution of RXRs to cardiac metabolism remains unknown. To explore such contribution, cardiac-specific RXRs deletion was induced, and the differences on adults and neonate mice hearts metabolism, were evaluated compared to wild-type mice using a non-targeted metabolomics approach with GC-MS and LC-MS. Frozen pieces of adult hearts, and the whole newborn organ (5 mg in average) where homogenized, and from the same homogenate aliquots were processed in parallel for GC-MS(Q) and LC-MS(qTOF) analysis. Raw data from by GC-MS were deconvoluted, aligned and integrated, and metabolites were annotated by comparison of fragmentation spectra with databases. For LC-MS data, molecular recursive feature extraction was performed for ion grouping and signal multialignment. Data matrices were exported for filtration, normalization, scaling and further univariate and multivariate (unsupervised and supervised) statistical analysis. In the case of LC-MS data, only relevant compounds were putatively annotated using CEU Mass Mediator (http://ceumass.eps.uspceu.es/) Results proved that there was a neat difference in the metabolic profile (amino acids, sugars, and lipids) between adults and newborns. Moreover, the different genotypes were strongly associated to the difference in the lipid profile, both in adults and newborns. Differences in the amino acid and central carbon metabolism between adults could be found, but in the newborn mice the profiles were similar in both genotypes.

P-86 Sex-specific metabolic adaptations to diminished nutrient supply

PRESENTING AUTHOR: Raphaela Fritsche, Berlin Institute of Health Metabolomics Platform and Max-Delbrück-Center for Molecular Medicine, Germany

CO-AUTHORS: Yoann Gloaguen, Cornelia Bartsch, Angelika Vietzke, Verena Stangl, Mario Lorenz, Jennifer Kirwan

Underlying molecular mechanisms for sex differences in the pathogenesis of cardiovascular diseases are poorly understood. In addition to hormonal influences, recent findings point to intrinsic sexual dimorphisms at the cellular level. To analyze sex differences in cellular responses to stress, we used male and female human endothelial cells from umbilical cords (HUVECs) from twin pairs. Previously, we had observed a greater ability of female HUVEC cells to form capillary-like structures compared to male cells. To investigate this further, a gas chromatography mass spectrometry (GC-MS) targeted approach was adopted to analyze HUVEC cells raised in different conditions. We focused on key metabolites associated with the central carbon metabolism (CCM). Untreated male HUVECs had a tendency towards slightly higher CCM pools compared to females. In contrast, female cells had altered levels of metabolite pools after serum starvation and VEGF suggesting better stress adaptation. Combined with our earlier findings of increased intracellular ATP levels and higher VEGF- induced migration in female cells, this suggests a higher or more efficient metabolic activity. This is further supported by a higher cell viability of female cells under serum starvation. We propose that female cells have an energetic advantage over male cells under conditions of diminished nutrient supply resulting in a superior ability to cope with nutritional stress and leading to an improvement in translating the VEGF signals into migration. This could have clinical implications for the treatment and prognosis of cardiovascular and other diseases.

P-87 Identification of biomarkers in Attention Deficit Disorder with or without Hyperactivity (ADHD)

PRESENTING AUTHOR: Patrick Emond, University of Tours, France

CO-AUTHORS: Camille Dupuy, Patrick Emond, Antoine Lefevre, Sylvie Mavel, Sylvie Bodard, Pierre Castelnau, Laurent Galineau

Attention Deficit Disorder Hyperactivity Disorder (ADHD) is a heterogeneous neuro-developmental disorder affecting 3-5% of school children and characterized by attention deficit, hyperactivity and impulsivity. Currently the diagnosis is made mainly using cognitive tests with a significant risk of diagnostic errors. Nowadays, no study has found reliable biomarker(s) for ADHD. The identification of biomarkers thus remains an important challenge for early diagnosis and appropriate therapeutic follow-up of patients. Associated with the search for circulating biomarkers, the study of central metabolism is crucial to better understand the pathophysiology of ADHD. As such, the use of animal models is relevant for studying the cerebral metabolome. The best characterized and most used rat model is the SHR / NCrl strain compared to the control strain WKY / NHsd. The objective of this study is to identify metabolic biomarkers, centrally and peripherally, in SHR / NCrl rats. For this, ten brain regions were taken, as well as peripheral samples (blood, urine and faeces), then analyzed in LC-HRMS. The data obtained were processed by multivariate, univariate analyzes and the discriminating metabolic pathways were searched. This study shows a discrimination between the two strains based on their metabolism. The metabolic pathway analysis makes it possible to differentiate two functional networks: the limbic ventral network and the cognitive dorsal network. In addition, the statistically significant alteration of common metabolic pathways is found in brain regions and peripheral compartments. Metabolomics studies on clinical peripheral samples will be carried out to better characterise this severe and frequent disorder.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

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BIOMEDICAL

P-88 **Effect of ASIC3 on metabolomics in serum and urine of fibromyalgia mice**

**PRESENTING AUTHOR:** Wei-Hsiang Hsu, China Medical University, Taiwan

**CO-AUTHORS:** Cheng-Han Lee, Yen-Ming Chao, Chih-Cheng Chen, Yun-Lian Lin

Fibromyalgia (FM) is a chronic widespread pain. The pathogenesis of FM is unclear. No specific biomarkers are available. Therefore, an animal models of FM may provide an opportunity to explore the potential biomarkers in a relative homogenous disease condition. Here, we probed the metabolomics in an intermittent cold stress (ICS)-induced FM mouse model and focused on the role of acid-sensing ion channel 3 (ASIC3), because ICS treatment induced chronic widespread muscle pain lasting for a month in wild-type ( ASIC3+/- ) mice, but not in ASIC3 knockout ( ASIC3-/- ) mice. Serum and urine samples were collected from both genotypes in different ICS stages, including before ICS (basal level, P0), and post-ICS at days 10 (middle phase, P10), and 40 (recovery phase, P40). 1H-NMR- and LC-MS-based metabolomics showed significant difference between control groups and ICS-induced FM groups. Pathway analysis demonstrated that leading regulated pathways in mice were taurine and hypotaurine metabolism, cysteine and methionine metabolism, glycerophospholipid metabolism, and ascorbate and aldarate metabolism. Further, an algorithm was developed for the most impact biomarkers in the FM model. They were cis-aconitate, kynurenate, taurine, pyroglutamic acid, pyrrolidonecarboxylic acid, and 4-methoxyphenylacetic acid in urine, as well as carnitine, deoxycholic acid, lysoPC (16:0), lysoPC (20:3), oleoyl-L-carnitine, and trimethylamine N-oxide in serum. Taken together, these results may serve as potential biomarkers for ASIC3-dependent FM diagnostic or therapeutic targets.

P-89 **Enhanced trans-sulfuration metabolically defines a distinct class of ALS patients**

**PRESENTING AUTHOR:** Qiuying Chen

**CO-AUTHORS:** Davinder Sandhu, Csaba Konrad, Dipa Roychoudhury, Benjamin I. Schwartz, Roger R. Cheng, Kirsten Bredvik, Hibiki Kawamata, Elizabeth L. Calder, Lorenz Studer, Steven. M. Fischer, Giovanni Manfredi

Amyotrophic lateral sclerosis (ALS) is a disease characterized by progressive paralysis and death. Most ALS cases are sporadic (sALS) and patient heterogeneity poses a formidable challenge for developing viable biomarkers and effective therapies. Applying untargeted metabolite profiling on 77 sALS-derived primary dermal fibroblast lines and 45 sex/age matched controls, we found a class of ~25% lines (sALS-1) were characterized by upregulated trans-sulfuration pathway, where methionine-derived homocysteine is channeled to cysteine and glutathione synthesis. sALS-1 fibroblasts exhibit a distinct growth defect in oxidative conditions, which is fully rescued by N-acetylcysteine. [U-13C]-glucose tracing shows that activation of the trans-sulfuration pathway is associated with accelerated glucose flux into the TCA cycle. Based on four metabolites, we developed a support vector machine model capable of distinguishing sALS-1 with 97.5% accuracy. Importantly, plasma metabolite profiling identifies a systemic perturbation of cysteine metabolism as a hallmark of sALS-1. These results indicate that sALS patients can be stratified into distinct metabolotypes, differently sensitive to metabolic stress, and provide new insights into metabolic biomarkers and personalized therapies for sALS.

P-90 **Tryptophan metabolite profile changes in multiple sclerosis**

**PRESENTING AUTHOR:** Ferenc Tömösi, University of Szeged Department of Medical Chemistry, Hungary

**CO-AUTHORS:** Gábor Kecskeméti, Edina Cseh, Elza Szabó, Cecília Rajda, László Vécsei, Tamás Janáky

Multiple sclerosis (MS) is disabling autoimmune, inflammatory neurodegenerative demyelinating disease affecting the central nervous system. Approximately 2.3 million patients with MS live in the world. Although some changes in tryptophan metabolite profile were associated with MS, we decided to investigate a wider range of metabolites in order to find biomarker(s) for early diagnosis of the disease. A short UPLC-tandem mass spectrometry method was developed for targeted analysis of twelve most important tryptophan metabolites (serotonin - SERO, kynurenine - KYN, 3-hydroxyanthranilic acid - 3-HANA, tryptophan - TRP, 5-hydroxyindoleacetic acid - 5-HIAA, anthranilic acid - ANA, kynurenic acid - KYNA, 3-hydroxykynurenine - 3-HK, xanthurenic acid - XA, melatonin - MELA, picolinic acid - PICA and quinolinic acid - QUIN) in human cerebrospinal fluid. To achieve absolute quantification stable isotope-labeled internal standards (d4-SERO, d4-KYN, d3-3-HANA, d5-TRP, d5-5-HIAA, d5-KYNA, d3-3-HK, d4-XA, d4-MELA, d4-PICA and d3-QUIN) were used. Three metabolites were analysed in derivatized form (3-HK, PICA and QUIN) together with nine underivatized ones. Following the official guidelines, a validation process was carried out to determine the intra- and inter-day precision and accuracy, to confirm the robustness and sensitivity of the developed method. Compared to the control group a dramatic increase of QUIN and decrease of KYNA concentration was observed in the MS group, resulting in a significant rising of QUIN/KYNA ratio. A significant increase in the KYN/TRP ratio was observed in MS patients, too. These results are in harmony with changes detected in human plasma.
<figure><img src="image_39.png" /></figure>

**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

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BIOMEDICAL

P-91 Pharmacokinetic studies and in-vitro metabolism in HepG2 and HepaRG cell lines of novel modafinil analogue CE-123 by LC-HRMS

PRESENTING AUTHOR: Iva Cobankovic, University of Vienna, Austria

CO-AUTHORS: Iva Cobankovic, Judith Wackerlig, Eva Maria Franschitz, Verena Johler, Carina Müller Predrag Kalaba, Gyertyán István, Gábor Brenner, Ernst Urban, Thierry Langer, Gert Lubec

Modafinil is a wake-promoting drug that has been used for the treatment of excessive sleepiness in patients with narcolepsy. There are several suggested hypotheses of Modafinil mechanism but most probably one is binding of Modafinil to the dopamine transporter (DAT). However, specificity of Modafinil for DAT is limited as it also binds to the serotonin and noradrenaline transporters. Recently, we synthesized a novel Modafinil analogue CE-123 with higher specificity for the DAT and tested its pharmacokinetic properties on aged rats and its metabolism in liver cancer cell lines (HepG2 and HepaRG). Plasma samples from aged rats were taken 2,5 hours after administration of 10 mg/kg CE-123 via intraperitoneal injection. In order to determine the concentration of CE-123, a LC-HRMS method was developed and validated applying Modafinil as internal standard. LOD and LOQ were found to be 2 and 6 ng/mL, respectively. The analyte concentrations were in a range of 1.2-4.1 µg/mL with a mean of 3.1 µg/mL (%CV = 3.20). In our previous study on young rats plasma concentrations after 1 hour of administration of 10 mg/kg CE-123 were 2.3 ± 1.0 µg/mL. The higher concentrations of CE-123 in aged rats could be because of slower metabolism of aged animals. Biotransformation of CE-123 was observed in HepG2 and HepaRG cell lines. After 24 h incubation of HepG2 and HepaRG with CE-123 concentration of analyte decreased for 14% and 3,6%, respectively. An accurate and precise validated analytical method was developed enabling to observe pharmacokinetic properties and biotransformation of novel Modafinil analogues.

P-92 LC-MS Untargeted Analysis in Posttraumatic Stress Disorder

PRESENTING AUTHOR: Marcela Konjevod, Rudjer Boskovic Institute, Division of Molecular Medicine, Laboratory of Molecular Neuropsychiatry, Croatia (Hrvatska)

CO-AUTHORS: Jorge Saiz, Matea Nikolac Perkovic, Gordana Nedic Erjavec, Dubravka Svob Strac, Lucija Tudor, Neven Zarkovic, Coral Barbas, Nela Pivac

Posttraumatic stress disorder (PTSD) is a mental disorder that often develops after traumatic experience. It is a serious neuropsychiatric disorder characterized with impairments in feeling, thinking, sleeping and normal functioning. Molecular and biological basis of PTSD development and progression is still unclear. The aim of this study was to determine metabolites as possible biomarkers that differ between PTSD subjects and healthy controls. LC-MS (Q-TOF) was used for the analysis of the plasma samples of patients enrolled in this study (50 PTSD subjects and 50 healthy controls) in an untargeted analysis. Sample preparation included protein precipitation with cold methanol : ethanol (1:1). Prepared samples were injected randomly with injection volume set to 10 µL at temperature of 4°C, while flow was set up at 0.6 mL/min. The analysis were performed in positive and negative ionization. The chromatograms were processed and tandem mass spectrometry was performed for compounds statistically significant (p<0.05) in order to identify them. Compounds that were tentatively annotated or identified according to the MS / MS analysis mostly belong to the compound group of glycerophospholipids, with glycerophosphocholines as the most common class among glycerophospholipids. Altered levels of glycerophospholipids indicate increased inflammation and impairments associated with cell membrane. Posttraumatic stress disorder is a complex anxiety disorder that affects the whole organism, therefore future studies are necessary to determine possible biomarkers or metabolic pathways associated with PTSD. In order to validate the compounds obtained in this study, the next step will include targeted analysis on a larger number of samples.

P-93 Clinical metabolomics - Similarities and differences between multiple sclerosis and Huntington's disease

PRESENTING AUTHOR: Stephanie Herman, Uppsala University, Sweden

CO-AUTHORS: Payam Emami Khoonsari, Valter Niemelä, Torbjörn Åkerfeldt, Ola Spjuth, Joachim Burman, Kim Kultima

The metabolome is the set of all metabolites present in a cell, tissue or body fluid in a given time point. It comprises all substrates and end products in the biochemical networks in our body and as it is the closest omics layer to phenotype, it is directly affected by any pathophysiological changes. As such, the metabolome is an excellent compartment to study diversions from the normal state. We have measured the metabolome of cerebrospinal fluid (CSF) from patients in different stages of multiple sclerosis and Huntington's disease as well as in control individuals. Both disease metabolomes were significantly different from the metabolome of control individuals, with area under the receiver operating characteristic (AUROC) curves of 0.79(±0.21) and 0.72(±0.14) for multiple sclerosis and Huntington's disease respectively, and demonstrated significant differences between disease stages (AUROC values of 0.83(±0.15) and 0.76(±0.17), respectively). Inter-group comparisons revealed multiple biochemical pathways that were being altered, including the tyrosine metabolism in Huntington's disease, and the tryptophan metabolism and pantothenate and CoA biosynthesis in multiple sclerosis. In common, the phenylalanine and the nitrogen metabolism were altered in both multiple sclerosis and Huntington's disease. Metabolomics is still a maturing field, which we believe has the potential of developing into something clinically useful. In this study, the metabolic signature of CSF was able to distinguish two neurological diseases from normal state as well as demonstrated differences between stages of the diseases.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

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BIOMEDICAL

**P-94** First-episode psychotic patients who gain weight in follow-up have increased markers of non-alcoholic fatty liver disease at baseline

PRESENTING AUTHOR: Matej Oresic, Örebro University, Sweden

CO-AUTHORS: Santosh Lamichhane, Alex Dickens, Cecilia Carlsson, Jaana Suvisaari, Oliver Howes, Jarmo Hietala, Tuulia Hyötyläinen

Schizophrenia is associated with a life expectancy reduction of 15-20 years, mostly due to the high prevalence of cardiovascular disease, type 2 diabetes and metabolic syndrome. Identification of psychotic individuals who are at highest risk of rapid weight gain and the associated development of metabolic co-morbidities is therefore a major challenge for public health. We have previously shown in a first-episode psychosis (FEP) prospective study in Uusimaa district in Finland (1) that those FEP patients who rapidly gained weight, had increased circulating lipids that were previously reported as biomarkers of non-alcoholic fatty liver disease (NAFLD) (2). Here we applied lipidomics in a prospective study comprising 48 controls, 44 FEP patients and 22 individuals at clinical-high-risk (CHR) for psychosis, from two study centres (Turku/Finland and London/UK). Lipidomics (UHPLC-MS) was applied in baseline serum samples, while body mass index (BMI) was assessed at baseline and after 12 months. Similarly as in previous study (1), we found that FEP patients who gained weight had at baseline, independent of obesity, significant increase of triacylglycerols with low double bond count and carbon number, as well as decreased phospholipids containing polyunsaturated fatty acids. Our study thus confirms that lipidomic signature of NAFLD at baseline, independent of obesity, may serve as a predictor of weight gain and may thus provide a useful marker for identifying patients who are most vulnerable to the development of metabolic co-morbidities in psychosis.

**P-95** Lipid profiles of first episode psychosis

PRESENTING AUTHOR: Alex Dickens, University of Turku, Finland

CO-AUTHORS: Santosh Lamichhane, Laurikainen H, Borgan F, Suvisaari J, Howes O, Hietala J, Hyötyläinen T, Matej Orešič

The metabolic co-morbidities in psychosis are well recognised. The underlying mechanisms for these metabolic changes remain unclear. Here we studied the circulating lipid profiles in 4 independent psychosis cohorts and controls. Two of the cohorts were from Finland (Turku and THL), one cohort from London (KCL) and one from Spain (SERMAS). Our aim was to identify changes in lipids in first episode psychosis (FEP) individuals compared to the controls. The lipids were detected using a UHPLC-QTOF (Agilent 6540) profiling method. The concentrations of the lipids were calculated using class based internal standards and standard curves. The Turku and KCL samples were run in the same batch and used as a discovery cohort (n=57). The THL (n=38) and SERMAS (n=130) were used as independent validation cohorts. The lipid profiles showed a clear effect of site between the Turku and KCL groups. The Gaussian clusters revealed that the main lipids driving this separation were triglycerides suggesting a diet effect in these two populations. There was also a significant effect of gender in the lipid clusters and therefore, we decided to model the genders separately. In the male FEP patients 4 lipids were identified by univariate and multivariate analysis. The 4 lipids were PC (40:5), PC(40:4), PC(32:1), PC(38:6) and all decreased in concentration in FEP. Meta-analysis across all 4 cohorts reveal that these lipids are regulated similarly across the cohorts. These lipid species identified by this study can demonstrate a unique lipid signature for the onset of FEP in a multi-centre setting.

**P-96** Analysis of ceramides and sphingosine 1 phosphate in ischemic stroke patients using ultra-high-pressure liquid chromatography - electrospray ionization tandem mass spectrometry

PRESENTING AUTHOR: Tsung-Heng Lee, School of Pharmacy, National Taiwan University, Taiwan

CO-AUTHORS: Sung-Chun Tang, Hsi-Chun Chao, Ching-Hua Lee, Ching-Hua Kuo

Sphingolipids are major constituents in eukaryotic cell membrane and play many key roles in cellular regulation processes, which is also involved in pathophysiological mechanism of many diseases. Increasing evidence has shown that the sphingolipids involved in the development of ischemic stroke and the sphingolipid pathway may act as the potential therapeutic targets. To provide accurate sphingolipid quantification results, we have optimized the sample extraction protocol and the ultra-high-pressure liquid chromatography - electrospray ionization tandem mass spectrometry (UHPLC-ESI-MS/MS) analytical method. To investigate the prognostic roles of ceramide in patients with acute ischemic stroke, we collected plasma samples from acute ischemic stroke patients at 24 hr and 72 hr post stroke (n=95; poor prognosis: 46%) and non-stroke controls (n=55). Plasma samples were measured by the optimized UHPLC-ESI-MS/MS method. The post-stroke outcome was determined by the modified Rankin Scale (mRS), and mRS 0-2 at 3 months post stroke was defined as a good outcome. The preliminary results show that the levels of sphingosine-1-phosphate in patients significantly decrease compared to the control group. The comparison of ceramides with different acyl chains between patients with different outcomes at 72 hours revealed a significant increase of long-chain ceramide levels, C16, C18, C20, and C22 in patients with poor prognosis. These results suggest long chain ceramides represented as potential prognostic markers for patients with acute ischemic stroke. The biological mechanism of long chain ceramides in ischemic stroke deserves further investigation to elucidate their role as the therapeutic target.
<figure><img src="image_40.png" /></figure>

**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

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BIOMEDICAL

P-97 Profiling metabolites in rat brain microdialysates by capillary electrophoresis-mass spectrometry using direct sample injection

PRESENTING AUTHOR: Marlien van Meyer, Leiden University, Netherlands

CO-AUTHORS: Thomas Hankemeier, Rawi Ramautar.

Analysis of low-molecular-weight biomolecules in brain extracellular fluid plays an important role in the prediction, progression, and treatment outcome for various neurological diseases. Microdialysis is a powerful technique for in vivo sampling of extracellular fluid in the brain, thereby enabling the continuous measurement of neurotransmitters in freely-moving animals. However, metabolic analysis of microdialysis samples can be considered a huge analytical challenge due to limited sample amounts and low basal (nanomolar-range) concentrations of many metabolites. In this study, we have developed a capillary electrophoresis-mass spectrometry (CE-MS) method for the profiling of amino acids and related compounds in rat brain microdialysates using direct sample injection. CE was coupled to time-of-flight mass spectrometry (TOF-MS) employing a co-axial sheath-liquid interface and a bare fused-silica capillary. Amino acids were analyzed at low-pH separation conditions using 10% acetic acid (pH 2.2) as separation buffer. To increase the concentration sensitivity of CE-MS, an in-capillary preconcentration procedure was applied, which allowed large volume sample injections. The developed CE-MS system allowed the direct analysis of amino acids in rat brain microdialysis samples after only applying a centrifugation step. Low nanomolar detection limits could be obtained for the compounds with minimal sample matrix effects. Overall, we propose here the first CE-MS method for the direct profiling of amino acids and related compounds in rat brain microdialysate samples. The utility of this approach will be tested by analyzing a large set of rat brain microdialysate samples in a pharmacokinetic and biomarker discovery context using metabolomics.

P-98 Impact of preservation conditions on the fecal metabolome and lipidome

PRESENTING AUTHOR: Margot De Spiegeleer, Ghent University, Belgium

CO-AUTHORS: Steve Huysman, Lieven Van Meulebroek, Lynn Vanhaecke

Eminent attention towards fecal fingerprinting is emerging, in that it may unravel the symbiotic interplay between the host, diet and intestinal ecosystem and yield characteristic signatures of responsive metabolic discrepancies regarding gut (patho)physiology and beyond. However, it is instrumental to capture and conserve a realistic snapshot that is reflective for the dynamic metabolome covered upon (outpatient) sampling to circumvent erroneous interpretations and subsequent deceptive associations regarding the disease and parameter(s) under observation. Hence, this study tackles the present-day lack of preservation guidelines regarding the stability of the fecal polar metabolome and lipidome, using in-house developed and validated extraction and UHPLC-HR-Q-Orbitrap-MS methods (Vanden Bussche et al., 2015 & Van Meulebroek et al., 2017, Anal. Chem.). By means of targeted profiling (n>400) and untargeted fingerprinting in concert with univariate and multivariate data analysis, the effect(s) of freeze-thawing (up to 2 cycles) and storage duration (up to 25 weeks), integrated with storage temperature (-20°C and -80°C) and (an)aerobicity were assessed. For the polar metabolome fraction, the impact of aerobicity was concluded to be negligible, which was ascribed to lyophilization of the fecal material. Conversely, freeze-thawing was pointed out to significantly affect metabolome composition with the first cycle being predominant. For example, elevated concentration levels were observed for amines and amino acids. Monitoring the long-term stability, particularly the low-molecular-weight metabolites (<400 Da) exhibited significant alterations during the timecourse of storage, whereby our recommendation sounds to store lyophilized fecal samples no longer than 4 weeks at -20°C and 8 weeks at -80°C.

P-99 Nuclear Magnetic Resonance Urine Metabonomics of Healthy Taiwanese Subjects from the Taiwan Biobank

PRESENTING AUTHOR: Chung-ke Chang, Taiwan Biobank, Taiwan

Human urine is one of the most accessible and information-rich biofluids for metabonomic studies. Many studies have been conducted on the correlation between urine metabonomics and various diseases, but there is little information on the characteristics of the urine metabolome of "healthy" subjects from distinct ethnicities. Establishing such an ethnic "reference metabonome" is necessary for the development of metabonomic applications in a population-wide precision medicine context. Nuclear magnetic resonance (NMR) spectroscopy is especially suited to the task because of its easy sample handling and excellent reproducibility. We hand-picked a set of healthy and fit individuals from participants enrolled in the Taiwan Biobank project and obtained a preliminary reference metabonome NMR spectrum representing ethnic Han Chinese residing in Taiwan. We highlight spectral regions with low variance across the samples, which may represent a population fingerprint of health for Taiwanese individuals. We also compare our findings with results from other population cohort urine metabonomics initiatives.
<figure><img src="image_41.png" /></figure>

**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

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BIOMEDICAL

P-100

Metabolomic biomakers of smoking habit in a large population study in Japan: Tsuruoka Metabolomics Cohort Study

PRESENTING AUTHOR: Sei Harada, Keio University, Japan

CO-AUTHORS: Ayako Kurihara, Mizuki Sata, Minako Matsumoto, Suzuka Kato, Takuma Shibuki, Miho Iida, Ayano Takeuchi, Akiyoshi Hirayama, Masahiro Sugimoto, Tomoyoshi Soga, Masaru Tomita, Tomonori Okamura, Toru Takebayashi

[Background and Aim] Smoking causes various health impairment. Recently, new tobacco products such as e-cigarette and heat-not-burn tobacco are becoming popular, but their chronic health effects are not well known. To establish novel methods to evaluate effects by these new products is demanded. Metabolomics is one of promising approaches to find biomarkers of health effects by smoking habit. Therefore, we examined metabolomic biomarkers of smoking effects in a large population-based cohort in Japan. [Methods and Results] We conducted metabolomic profiling by capillary electrophoresis-mass spectrometry (CE-MS) for 10,933 fasting plasma samples of community dwelling participants of the Tsuruoka Metabolomics Cohort Study in Japan. Ninety-four polar metabolite concentrations were absolutely measured. After excluding participants with history of cancer, stroke and ischemic heart disease, 4,573 males and 5,338 females (35-74 years old) were included in this study. Linear mixed model showed that 48 metabolites in males and 28 in females were different between current and never smokers after adjusting age and other confounders as fixed effect and metabolome analysis batch as random effect (FDR-p <0.05). Twenty-two metabolites were common biomarker candidates for both genders. Past smokers had intermediate profile between current and never smokers. Two of these metabolites had clear dose-dependent associations with smoking numbers per day among current smokers. Also, two metabolite concentrations were associated with period after smoking cessation. [Conclusion] Our CE-MS metabolomics platform discovered biomarker candidates related to smoking habit. Found dose and time dependent association suggests that these biomarkers are reliable to evaluate chronic health effect by smoking.

P-101

Metabolomic approach to investigate alteration in metabolites associated with 25-hydroxyvitamin D in healthy Korean adults

PRESENTING AUTHOR: Mi-Ri Gwon, Kyungpook National University, South Korea

CO-AUTHORS: Bo Kyung Kim, Seungil Cho, Sook Jin Seong, Young-Ran Yoon

Vitamin D3 (cholecalciferol) deficiency is prevalent in Korean and affects up to 80% of Korean adults. This vitamin is important to avoid the risk of other health problems including chronic autoimmune, infectious diseases, cancer, cardiovascular disease, and diabetes. Most previous studies focused on finding intermediate metabolites of vitamin D3. To understand the metabolic pathway of vitamin D3, it is important to investigate its association with endogenous metabolites in elderly or osteoporosis-risk groups. Thus, we examined the association between serum level of primary metabolite, 25(OH)D and metabolite alteration in healthy Korean adults for preliminary study. Forty-five healthy Korean adults were divided into two groups based on average serum levels of 25(OH)D: high (n=21, 23.0 ng/mL) and low (n=24, 10.4 ng/mL) groups. Demographic, anthropometric, and blood profile parameters were measured. Metabolic profiling was performed using UHPLC-QTOF/MS and multivariate statistical analysis. The altered metabolites were determined and identified using MetaboScape software. No significant differences were observed in demographic, anthropometric, and blood profile parameters between two groups. After preprocessing UHPLC-QTOF/MS data, we obtained 55,940 spectral features for untargeted metabolomic analysis. Score plots of both principal component analysis and orthogonal projections to latent structures-discriminant analysis showed a tendency for two groups to be separated. In this analysis, R2 (goodness of fit) and Q2 (predictability) were 0.280 and 0.234, respectively. Five endogenous metabolites were finally identified. Further research with larger sample sizes and other clinical trial designs (e.g., administration of 25(OH)D to osteoporotic or elderly people) is required before a solid conclusion can be reached.

P-102

Metabolomic Profiles Associated with Body Mass Index, Waist Circumference, and Diabetes and Inflammation Biomarkers in Older Adults

PRESENTING AUTHOR: Victoria Stevens, American Cancer Society, United States

CO-AUTHORS: Brian D. Carter, Marjorie M. McCullough, Peter T. Campbell, Ying Wang

Metabolomic profiling has been used to identify metabolites altered in overweight and obese individuals but the roles of these metabolites in the development of obesity-related diseases is unclear. To address this, an untargeted, mass spectroscopy-based metabolomic analysis was conducted using serum from 1,534 women and plasma from 554 men aged 53-86 years. Linear regression was first used to identify metabolites associated with body mass index (BMI) and waist circumference (WC) in women and men separately. Next, among these metabolites, blocks of clustered metabolites whose association with the anthropometric measures could be represented by a single metabolite were defined. The association of these representative metabolites with biomarkers for diabetes and inflammation was then determined. Statistically significant associations with BMI and WC were observed both for previously identified metabolites and novel metabolites, including several sphingolipids, nucleotides, and modified fatty acids. Identification of clustered blocks reduced the number of metabolites associated with BMI in women from 260 to 115 and, in men, from 79 to 22. Specific adiposity-associated metabolites were also associated with clinical biomarkers, including a choline-containing plasmalogen (O-16:0/18:1) with c-peptide and adiponectin and glycine with c-reactive protein, suggesting they might contribute to insulin regulation and resistance and inflammation. These results add to the list of metabolites associated with adiposity and indicate which may influence processes that contribute to the development of obesity-related diseases. In addition, the identification of clusters of metabolites using a correlation-based method indicated common chemical features that may help explain their association with the anthropometric measures.
<figure><img src="image_42.png" /></figure>

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BIOMEDICAL

P-103

Is there a metabolomic signature indicative of human urine specimen degradation? A systematic review

PRESENTING AUTHOR: Ana Rosen Vollmar, Yale School of Public Health, United States

CO-AUTHORS: Caroline H. Johnson

With metabolomics increasingly used to investigate the exposome, interest is growing in using biobanked samples and other specimens in long-term storage. Specimen quality can vary due to handling procedures, storage conditions, and freeze-thaw cycles. We conducted the first systematic review of whether there is a metabolomic signature of human urine specimen degradation. Using controlled vocabulary terms and text words, studies were identified through PubMed and Web of Science. Seventeen studies met the inclusion criteria of using human urine, and comparing conditions of storage time, temperature, and freeze-thaw cycles. We developed a study quality rating system based on the Metabolomics Standards Initiative. Study quality varied but was generally moderate to high, lending support to our findings. While targeted analyses found significant metabolite changes across comparison groups, untargeted analyses found no meaningful changes in the global metabolomic profile, with biological variability the primary source of variability between specimens rather than handling and storage conditions. More than 2-3 freeze-thaw cycles may alter metabolite composition in targeted studies, but untargeted analyses are robust to even 9 freeze-thaw cycles. Minimal difference was observed between specimens stored at -20 °C and -80 °C. Specimens remained stable for 6 months at -25 °C or -80 °C, but no studies examined storage longer than 6 months. A total of 90 metabolites associated with handling and storage conditions were identified across all studies, with 19 identified by at least 2 studies, indicating there is not yet a clear metabolomic signature of urine degradation, but offering directions for future research.

P-104

Sugars and derivatives in the human metabolome: what they can tell us

PRESENTING AUTHOR: Carina Mack, Max Rubner-Institut, Germany

CO-AUTHORS: Christoph H. Weinert, Hannelore Daniel, Sabine E. Kulling

Sugar compounds (mono- and disaccharides, polyols and sugar acids) are part of the metabolome. Although numerous sugar compounds occur in nature, mostly only a very few common and well-known compounds are analyzed. Metabolomics often requires a compromise between detecting as many different metabolites and substance classes as possible, and satisfactory separation of compounds within each substance class. Sugars with their high structural similarity present a particular challenge with usually insufficient chromatographic and mass spectrometric separation. More comprehensive and highly selective methods to assess the diversity of the human body fluid sugar profile are thus needed because sugar compounds may serve as markers of dietary intake and may act as reporter molecules of the health status. We developed a semitargeted GC-MS based profiling method enabling detection of known and unknown sugar compounds in urine and plasma. 24 h urine samples of the observational Karlsruhe Metabolomics and Nutrition study with 300 healthy participants were analyzed and markers for dietary intake were identified amongst the sugars, such as mannoheptulose and perseitol for avocado consumption. In an additional intervention study including an oral glucose tolerance test, plasma samples of healthy, prediabetic and diabetic participants were analyzed and revealed, next to glucose, a variety of sugars and derivatives with marked postprandial differences dependent on health status, such as trehalose. Overall, the application of the sugar profiling in these human studies revealed a more complex sugar profile than described or expected so far with potential for finding novel markers.

P-105

Metabolic phenotyping of individuals in baseline and repeat surveys of Tohoku Medical Megabank Cohort Project

PRESENTING AUTHOR: Seizo Koshiba, Tohoku University, Japan

CO-AUTHORS: Daisuke Saigusa, Ikuko Motoike, Jin Inoue, Eiji Hishinuma, Matsuyuki Shirota, Yuichi Aoki, Shu Tadaka, Kengo Kinoshita, Masayuki Yamamoto

Tohoku Medical Megabank (TMM) Project operates prospective cohort studies for more than 150,000 individuals in Japan. We have finished baseline surveys and are now conducting repeat surveys. We are also operating genome and omics analyses for the cohort participants and have already collected whole genome sequences data from more than 5,000 participants and the metabolome data from more than 10,000 participants. We have released these results as a database, Japanese Multi Omics Reference Panel (jMorp), which is freely available on the web site (https://jmorp.megabank.tohoku.ac.jp/). In this conference, we report recent progress of our metabolome analyses in the TMM project. We expanded our metabolome analysis and will release NMR metabolome data from more than 15,000 participants at the baseline survey this year. We also quantified more than 1,000 participant's plasma metabolites by means of LC-MS/MS and will also release these results. On the other hand, we have performed metabolome analysis for participants at the repeat assessment survey and will show the changes of metabolic phenotypes of individuals between the baseline and repeat surveys. We are also performing metabolome genome-wide association study (MGWAS) and other association studies. We suggest the importance of the long-term examination of metabolome analysis for the large scale prospective cohort studies.
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BIOMEDICAL

P-106

Metabolomic Amino Acids Profiles as Biomarkers to Identify Metabolic Alterations

PRESENTING AUTHOR: Dirce Maria Marchioni, University of São Paulo, Brazil

CO-AUTHORS: Dirce Maria Marchioni, Regina Mara Fisberg, Alexsandro Macedo Silva

Background. Metabolic alterations compromise physiological functions, triggering morbidities for humans. Therefore, would be valued to explore biomarkers to recognise metabolic changes using the metabolomics tools. Objective. This study aimed to investigate amino acids (AA) as biomarkers to classify metabolic variations. Methods. Blood samples were obtained from 168 adults (≥20 years) who participated in the population based cross-sectional study "Health Survey of Sao Paulo". The targeted AA metabolome profiling was analysed by HPLC/MS methods. Principal Component Factor Analysis (PCFA) with varimax orthogonal rotation was performed to generate the AA patterns. Obesity was determined based on Body Mass Index ≥30 kg/m². HOMA-IR was estimated, considering the cut-off ≥2.7 for insulin resistance (IR) classification. Metabolic Syndrome (MS) was characterized by 3 or more health abnormalities parameters, such as medicine use, blood pressure (≥130mmHg/85mmHg), fasting glucose (≥110mg/dL), triglycerides (≥150mg/dL), HDL-cholesterol (≤40mg/dL for men; ≤50mg/dL for women), and waist circumference (≥102cm for men, ≥88cm for women). The dyslipidaemia (DL) variable was considered one or more factors as followed: LDL-cholesterol (≥160mg/dL); Total Cholesterol (≥190mg/dL); triglycerides (≥175mg/dL). The ability of the AA to discriminate the outcomes was assessed by using area under the receiver operating characteristic curve (AUC). Results. The PCFA produced 5 profiles (P), but only the P1 (Leu, Val, Ile, Phe, Tyr, Trp, Lys, Met, His, Glu, Gly, Asn, Ala), which represented the β-catabolism of AA and lipids showed a promising outcome classification: IR (AUC=0,604); MS (AUC=0,657); Obesity (AUC=0.744); DL (AUC=0.622). Conclusion. The AA pattern revealed a noteworthy characteristic as biomarker for metabolic changes.

P-107

Effects of chronic hypervitaminosis A on global plasma metabolome changes in pig and human

PRESENTING AUTHOR: Warwick Dunn, University of Birmingham, United Kingdom

CO-AUTHORS: Georg Lietz, Anthony Oxley, Kieran Finney, Adam Clark, Tim Giles, Neil Foster, Andrew Southam, Andris Jankevics, Gavin Lloyd, Catherine Winder, Elliot Palmer

Objectives: Significant concerns about inadvertent chronic excessive vitamin A (VA) intakes due to overly frequent supplementation, fortification and voluntarily fortified products have been raised with primary impact being observed in the Developing World. Clinically detectable signs of VA toxicity are rare, indicating the need for early biomarkers of tissue damage induced by excessive VA intake. Here we will present two studies in pigs and humans. Methods and results: Study 1: To identify early putative markers of VA toxicity, we induced chronic hypervitaminosis A in pigs (64 pigs, 8 per group) dosed with an oral supplement of retinyl propionate (0 up to 10,000µg/KgBW) for 17 weeks. Two untargeted UPLC-MS assays (HILIC and C18 reversed phase) were applied to analyse plasma and urine metabolites followed by univariate and multivariate analysis. Multiple metabolite classes were perturbed primarily focused on lipid metabolism, including (lyso)glycerophospholipids, ceramides and acyl glycerides. Study 2: To identify markers of vitamin A stress we undertook two independent human studies) in Guatemala and the Phillipines (n>150 subjects in each study). Serum and dried serum spots were collected from children and one untargeted UPLC-MS assays (C18 reversed phase) were applied to analyse plasma and urine metabolites followed by univariate and multivariate analysis. Markers indicative of increased blood retinol levels included (lyso) glycerophospholipids, ceramides and acyl glycerides as was observed for the pig study. Conclusions: Potential markers of vitamin A levels and hypervitaminosis A have been identified in a pig model and validated in two independent human studies.

P-108

Chronic alcohol consumption causes dysregulation of the bile acid biosynthesis pathway

PRESENTING AUTHOR: Georgia Charkoftaki, Yale School of Public Health, United States

CO-AUTHORS: Georgia Charkoftaki, Wan Ying Tan, Jaya Prakash Golla, Pablo Berrios-Carcamo, David Orlicky, Vasilis Vasiliou

Alcohol consumption leads to tissue damage. However, the molecular mechanisms contributing to the damage remain to be fully understood. Our goal was to identify pathways affected in the liver caused by chronic alcohol consumption. Eight – 10 wk old male C57BL/6J mice were fed a modified ethanol-containing liquid diet Lieber-DeCarli (LD) (ethanol-treated, n=4) or an ethanol-free LD diet (control, n=5) for 6 wks. Mice on the ethanol diet started at 2% (v/v) and ethanol was increased 1% weekly over 5 wks, until 6% (v/v) was applied. At the end of the sixth week, the livers collected underwent histological examination and untargeted metabolomic analyses. Multivariate analyses determined differences in the metabolic profiles between ethanol-treated and control mice. Targeted metabolomic analyses was subsequently performed to quantify significant features uncovered in the untargeted metabolomic analyses. Histological examination revealed no inflammatory or injury differences; however, enlarged bile ducts were observed in the ethanol-treated mice. The most prominent change in the metabolic profile of ethanol-treated mice occurred in the bile acid biosynthesis pathway. Utilizing targeted metabolomics, we quantified 19 bile acids. Of these, significant (P<0.05) increases in the primary bile acid cholic acid (5.0-fold), and its taurine- and glycine- conjugated bile acids, including taurodeoxycholic acid (2.0-fold), taurohodeoxycholic acid (3.0-fold), glycocholic acid (11.5-fold) and glycochenodeoxycholic acid (4.8-fold) were observed in the ethanol-treated mice. Our study provides new insights into hepatic changes occurring early during chronic alcohol consumption. How the dysregulated bile acid pathway may contribute to liver damage remains to be established.
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P-109

Patterns in metabolite profile are associated with risk of more aggressive prostate cancer: a prospective study of 3057 matched case-control sets from EPIC

PRESENTING AUTHOR: Julie Schmidt, University of Oxford, United Kingdom

CO-AUTHORS: Georgina K. Fensom, Sabina Rinaldi, Augustin Scalbert, Paul N. Appleby, David Achaintre, Audrey Gicquiau, Marc J. Gunter, Pietro Ferrari, Aurora Perez-Cornago, Timothy J. Key, Ruth C. Travis

Metabolomics may reveal novel insights into the aetiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3057 matched case-control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR[1SD]) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterised by higher concentrations of either phosphatidylcholines and hydroxy sphingomyelins (OR[1SD]=0.77, 95%CI 0.66-0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR[1SD]=0.72, 0.57-0.90), or lysophosphatidylcholines (OR[1SD]=0.81, 0.69-0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR[1SD]=0.77, 0.61-0.96). No associations were observed for prostate cancer overall or less aggressive tumour subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumours and prostate cancer death, and might be relevant to aetiology of advanced stage prostate cancer.

P-110

Metabolic profiling of mice cerebral tissue for the study of acute and chronic ethanol toxicity

PRESENTING AUTHOR: Emily Armitage, Shimadzu Corporation, United Kingdom

CO-AUTHORS: Helen Gika, Olga Deda, Christina Virgiliou, Georgios Theodoridis, Ian Wilson, Stephane Moreau, Neil Loftus

Alcoholic liver disease remains a leading cause of chronic liver disease, with increased morbidity and mortality. In recent years, biomarkers discovered through metabolomics have shed light on disease biochemistry, arousing interest in ethanol-induced biochemical perturbations. In this study the metabolic profiles of mouse cerebral tissue following short- or long-term ethanol exposure were analyzed. The long-term experiment (8 weeks) consisted of C57BL/6 mice (8-10 weeks old) separated into control and ad libitum feeding with a Lieber-DeCarli ethanol diet group for 8 weeks containing daily 5% alcohol 99%. The short-term animal experiment was conducted over 11 days. In addition, a single dose by oral gavage of 25% alcohol, at the 5th day of the intervention and at the last day of experiment 6 hours before sacrifice were administrated. The experiment was conducted in agreement with current national and European legislation (N. 2015/1992, ΠΔ 56/2013, European guideline 2010/63) and cerebral tissues were collected postmortem. Untargeted metabolic profiling analysis was performed using HRAM Q-TOF-MS (LCMS-9030, Shimadzu) with precursor and product ion scanning at 50 spectra per second within a mass range of m/z 50-1000. Univariate statistical analysis revealed that the short-term experiment decreased arachidonic acid, docosahexaenoic acid, glycerophosphocholine, CDP-choline, adenine, adenosine, cytidine, creatine, creatinine, valine and taurine along with some phospholipids. Long-term exposure decreased acetyl-carnitine, adenine and adenosine with phospholipids and ceramides, while many amino acids were increased along with hypoxanthine, xanthine, oxoproline, choline, creatinine, and docosahexaenoic acid. Metabolomics has proven to be a useful tool in elucidating the toxic effect of alcohol consumption.

P-111

Targeted metabolomics reveals training level specific metabolic adaptations in marathon race athletes

PRESENTING AUTHOR: Mark Haid, Helmholtz Zentrum Muenchen, Molecular Endocrinology and Metabolism, Germany

CO-AUTHORS: Jana Schader, Alexander Cecil, Julia Schoenfeld, Martin Halle, Arne Pfeufer, Jerzy Adamski, Johannes Scherr

**Objectives:** We were interested in characteristic patterns of metabolism in periods of preparation for and participation in a marathon race of 76 male athletes at different performance levels. **Methods:** We used a targeted metabolomics approach to analyse blood plasma samples of 76 male subjects who participated in the Munich marathon in 2013 (Enzy-MaGIC-Study). Metabolic changes were analysed at two different time points before and three time points after the marathon race. To reveal characteristic features between runners at different training levels, the cohort was stratified into top, average, and low performers based on general endurance (relative VO2max) and net running time during the marathon race. **Results:** In general, we observed increased concentrations of acylcarnitines (AC) and reduced concentrations of amino acids (AA) and phospholipids (PL) immediately after the race when compared to pre-exercise levels. In the following 24 hours and 72 hours a massive supercompensation of AA and PL levels became apparent. Furthermore, the metabolite profiles revealed performer class related characteristics in terms of the different periods of structured exercise. Most pronounced differences between performer classes were observed for acylcarnitines and urea cycle related amino acids immediately after the race. In conclusion, our study shows characteristic metabolite patterns between pre- and post-marathon race time points and reveals performance-dependent differences with regards to marathon-induced changes of the metabolome.
<figure><img src="image_43.png" /></figure>

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P-112

Differentiation of Fasting and Non-fasting Plasma Samples by Informative Metabolite Sets

PRESENTING AUTHOR: Patrick Dreher, Helmholtz Center Munich, Germany

CO-AUTHORS: Johannes Raffler, Thomas Skurk, Hans Hauner, Robert Mohney, Hannelore Daniel, Karsten Suhre, Gabi Kastenmüller

Blood metabolites are easily accessible biomarkers that can extend routine clinical chemistry. The utilization of non-fasted blood samples considerably simplifies blood sampling for patients and clinicians. However, the metabolite readout reflects the current metabolic status with substantial differences between fasted and fed states, which need to be considered for clinical interpretation. Additionally, dietary intake has shown to increase subject variability. Therefore, it is vital to know the fasting status at the time of sampling. We propose two machine learning prediction models that provide an objective differentiation of plasma samples into non-fasting (less than 4h or 6h postprandial) and fasting states. We used an iterative random forest approach with backward variable selection, trained on the time-resolved HuMet dataset comprising 56 time points with four different meal and fasting periods in 15 healthy men. In this study, a total of 595 metabolites were identified by non-targeted mass spectrometry-based metabolomics. The 4h prediction model contains nine metabolites that display two distinct mirror-like kinetic patterns: The first group of metabolites including glucose, fructose, and 3-hydroxy-3-methylglutarate, demonstrates elevated metabolite levels during non-fasting and low levels during fasting time points. Six fatty acids (mostly medium-chain) demonstrate a mirror-inverted behavior to the first group. In addition to the same six fatty acids, our 6h prediction model includes nucleotides and bile acids, which show comparatively slower postprandial changes in blood levels. Notably, our models can classify plasma samples with a low error rate (< 8,4%). The usability of our prediction models will be validated in large cohort studies.

P-113

NMR based metabolic analysis of human blood associated with particulate matter in air pollution

PRESENTING AUTHOR: Seoyoung Jang, Korea Basic Science Institute, South Korea

CO-AUTHORS: Juhwan Noh, Changsoo Kim, Geum-Sook Hwang

Particulate matter (PM) has become a major environmental risk factors all over the world, and related to human disease such as respiratory disease, nervous system disorder. We evaluate the change in response to environmental exposure and to investigate the association between concentrations of identified metabolite in human blood samples and PM with a diameter 2.5-10 µm (PM10). In this study, we analyzed human whole blood from 457 Koreans using 1H-NMR spectroscopy. We performed multivariate linear regression with the level of PM10 adjusted for age, sex, BMI, and smoking status. We found that PM10 was significantly altered energy metabolism such as succinate, pyruvate, lactate, and fumarate. This study demonstrated that NMR based metabolic profiling can be a useful tool and to assess the impacts of environmental pollutants on human metabolism and to identify potential biomarkers for predicting exposure of air pollution like PM10.

P-114

Metabolite profiling of multiple measures of adiposity: A Mendelian randomization analysis

PRESENTING AUTHOR: Matthew Lee, MRC Integrative Epidemiology Unit, University of Bristol, United Kingdom

CO-AUTHORS: Kaitlin Wade, Laura Corbin, Nicholas Timpson

The mechanisms by which obesity affects disease are poorly understood. Studying different adiposity measures together with intermediate phenotypes reflective of physiological function can provide valuable insight into complicated etiologic disease pathways. We investigated the causal effect of several adiposity measures on metabolic intermediates using Mendelian randomization (MR). This epidemiological approach uses genetic markers as proxy measures for exposures, to avoid typical limitations of observational analyses. A two-sample MR analysis was conducted using genetic variants for three exposures: body mass index (BMI), waist-hip-ratio (WHR), and body fat percentage (BF%). The outcomes comprised 123 metabolites derived from nuclear magnetic resonance spectroscopy. An inverse variance weighted multiplicative random effects model was applied. A newly developed web tool, MR-Vis (http://bristol-medical-stat.bristol.ac.uk:3838/MR-Vis/), was used to visualize and explore causal perturbations of metabolic profiles in relation to exposures. Across all three exposures, the direction of effect was consistent for 106 metabolites. BMI and WHR exhibited similar effects across a range of metabolites, including an inverse association with medium to large HDL and a positive association with a range of LDL and VLDL particles. Many of the results for BF% were consistent with the null. A positive association with glycoprotein acetyls and phenylalanine (P<0.05/123) was observed across all three exposures. The consistency observed in the relationship between different measures of adiposity and metabolic intermediates suggests some redundancy in these measures. However, where we see contrasting associations that can be mapped onto corresponding differences in disease susceptibility, our approach can provide insight into the biological mechanisms underpinning these differences.
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P-115

Joint analysis of metabolite markers of fish intake and persistent organic pollutants in relation to type 2 diabetes risk in Swedish adults

PRESENTING AUTHOR: Rikard Landberg, Chalmers University of Technology, Sweden

CO-AUTHORS: Lin Shi, Carl Brunius, Ingvar A. Bergdahl, Ingegerd Johansson, Olov Rolandsson, Carolina Donat Vargas, Hannu Kiviranta, Kati Hanhineva, Agneta Åkesson

Conflicting evidence exists regarding the association between fish intake and type 2 diabetes (T2D) incidence, potentially due to error-prone self-reported dietary intake assessments and co-exposure to persistent organic pollutants (POPs) present in fish. We identified plasma metabolites associated with fish intake and assessed their association with T2D risk, independently from co-exposure to POPs, in a case-control study nested in the Swedish prospective Västerbotten Intervention Programme cohort. Plasma samples from 421 case-control pairs at baseline and 10-year follow-up samples from a subset of 149 pairs were analyzed using untargeted LC-MS metabolomics. Moreover, 16 plasma POPs were analyzed for the sub-population (149 pairs). We identified 31 metabolites associated with fish intake using multivariate modelling and partial correlation analysis. No association was observed between fish intake either reflected by metabolites or measured by food frequency questionnaires, and T2D risk, using a conventional multivariate logistic regression adjusted for POPs. Interestingly, integrating fish-related metabolites and plasma POPs using two-way orthogonal partial least squares regression led to a unique metabolite component independent of POPs, which was borderline inversely associated with T2D risk (odds ratio:0.75; 95% CI: 0.54, 1.02, P=0.07). This component mainly reflected fatty fish intake and consisted of several species of phosphatidylcholines and phosphatidylethanolamines. Our results support that fatty fish may be beneficial for T2D prevention, although simultaneous co-exposure to POPs may counteract those effects in Swedish adults. Integrating metabolite markers and POP exposures appears a promising approach to advance the understanding of associations between fish intake and T2D incidence in populations co-exposed to POPs.

P-116

Plasma biomarkers of boiled and filtered coffee intake and their association with type 2 diabetes risk

PRESENTING AUTHOR: Carl Brunius, Chalmers University of Technology, Sweden

CO-AUTHORS: Lin Shi, Ingegerd Johansson, Ingvar A. Bergdahl, Olov Rolandsson, Kati Hanhineva, Rikard Landberg

Habitual coffee intake has been associated with a lower risk of developing type 2 diabetes (T2D), but only few studies have investigated different coffee brews, i.e. boiled and filtered, separately. We identified metabolites related to either filtered or boiled coffee, and assessed their association with T2D risk in a nested case-control study within the Swedish prospective cohort Västerbotten Intervention Programme. Plasma samples from 421 case-control pairs at baseline and from a subset of 149 pairs at 10-y follow-up were analyzed using untargeted LC-MS metabolomics. We identified 31 metabolites that were associated with boiled- (0.1≤ IrI ≤ 0.47) and 30 associated with filtered coffee intake (0.1≤ IrI ≤ 0.34), respectively, using multivariate modelling and partial correlation analysis adjusted for life-style confounders. Among these metabolites, 14 and 10 were unbiasedly selected in panels by LASSO regression for accurate and specific prediction of boiled (AROC =0.91) and filtered coffee (AROC =0.90), respectively. Moreover, metabolite panels could also predict boiled and filtered coffee intake after 10-y of follow-up (AROC=0.71 and 0.80, respectively). Furthermore, we observed an inverse association between the metabolite panel score related to filtered coffee and T2D risk, independent of established risk factors and lifestyle confounders. No association was observed for boiled coffee. In summary, for the first time, we identified metabolite panels which might be used as selective biomarkers for boiled and filtered coffee intake, respectively. Our study supports a protective role of habitual intake of filtered coffee on T2D development.

P-117

Investigating in vivo digestion of sheep and cow milk in a rat model

PRESENTING AUTHOR: Linda Samuelsson, AgResearch Ltd, New Zealand

CO-AUTHORS: Linda Samuelsson, Natalie Ahlborn, Wayne Young

Sheep milk is a rich source of vitamins, minerals and energy, with up to 50% more milk solids than cow milk. Anecdotally, sheep milk is thought to be better tolerated than cow milk and some of these affects have been attributed to differences in milk protein digestibility. However, controlled scientific studies examining this potential difference are lacking. The purpose of this study was to compare the digestion of sheep and cow milk in terms of a) apparent ileal amino acid digestibility and b) metabolite profiles in serum and caecal contents in a rat model. Male Sprague-Dawley rats were fed a dairy-free rodent chow and provided with sheep or cow milk over a 28-day period. Serum, distal ileal content and caecal content were collected. Amino acid digestibility in the distal ileum at day 28 was higher in rats fed sheep milk; amino acid intake in sheep milk rats was 1.8 times higher, but the amino acid concentration in the ileal content was only 1.3 times higher. Concentrations of essential amino acids in serum were significantly higher in rats fed sheep milk, indicating that sheep milk proteins are more readily digested. In addition, rats fed sheep milk had higher concentrations of dimethyl sulfone, g-aminobutyric acid, amino acids and short-chain fatty acids in serum and caecal contents compared to rats fed cow milk indicating that ingestion of the two milks lead to different digestion products. The potential for these products to have differential effects on physiology and health is yet to be established.
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P-118 Lifestyle-intervention-induced reduction of abdominal fat is reflected by increased serum HDL diameter and decreased glycerol level

PRESENTING AUTHOR: Marian Beekman, Leiden University Medical Center, Netherlands

CO-AUTHORS: Marian Beekman, Bianca A.M. Schutte, Erik B. van den Akker, Raymond Noordam, Petra Dibbets-Schneider, Lioe-Fee de Geus-Oei, Joris Deelen, Ondine van de Rest, Diana van Heemst, Edith J.M. Feskens, P. Eline Slagboom

Abdominal obesity is one of the main modifiable risk factors of age-related cardiometabolic disease. Cardiometabolic disease risk and its associated abdominal fat mass, cholesterol and glucose levels can be reduced by a healthier lifestyle. Hence, our aim is to understand the relation between the lifestyle intervention induced changes in body composition, and specifically abdominal fat, and the accompanying molecular changes. Therefore, we used the data from the Growing Old Together (GOTO) study, in which 164 older adults (mean age 63 years, BMI 23-35 kg/m2) changed their lifestyle during 13 weeks by 12.5% caloric restriction plus 12.5% increase in energy expenditure. Here, we first show that the levels of circulating metabolic biomarkers specifically reflect the abdominal fat mass, even after adjustment for body mass index. Second, we show that the applied lifestyle intervention mainly results in reduction of abdominal fat (-2.6%, SD=3.0) and that this reduction, when adjusted for weight loss, is highly associated with an increase of the HDL diameter and decrease of circulating glycerol levels. To monitor the weight-loss-independent beneficial effects of lifestyle change, circulating glycerol levels and HDL diameter may be valuable tools.

P-119 Metabolic features of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

PRESENTING AUTHOR: Emi YAMANO, Health Metrics Development Team, RIKEN Compass to Healthy Life Research, Japan

CO-AUTHORS: Masahiro Sugimoto, Satoshi Kume, Yasuyoshi Watanabe, Tomoyoshi Soga, Lucinda Bateman, Suzanne D. Vernon, Yosky Kataoka

The pathogenesis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) characterized by exertional and severely debilitating fatigue with/without infectious or neuropsychiatric symptoms lasting at least 6 consecutive months is not fully understood. Because of incomplete understanding of aetiology and diagnostic uncertainty of ME/CFS, there are no firmly established objective diagnosis using biomarkers. In the present study, we performed comprehensive metabolomic analyses of plasma samples obtained from ME/CFS patients and healthy controls in the United States using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS). By reference to our previous findings of inactivity in tricarboxylic acid (TCA) and urea cycles in ME/CFS (Yamano E, 2016), we focused on the alterations of metabolite concentrations in these metabolic cycles. In ME/CFS patients, malate was increased and arginine was decreased relative to healthy controls. The female patients with ME/CFS notably exhibited abnormalities in TCA and urea cycles, compared with male patients. In addition, arginine/malate ratio discriminated female patients with ME/CFS from female healthy controls yielding area under the receiver operating characteristic curve values of 0.72 (95 % confidential interval: 0.61-0.72, P < 0.0001). This suggested that ME/CFS patients in the US may also have some dysregulation of TCA and urea cycles which reflects the pathophysiological state in line with our finding in Japanese samples, and that sex may be the significant factor in the development of the biomarker for ME/CFS. These findings will help to establish the objective diagnosis marker and treatment recommendations for ME/CFS.

P-120 Machine learning of human plasma lipidomes for obesity estimation in a large population cohort

PRESENTING AUTHOR: Christian Klose, Lipotype GmbH, Germany

CO-AUTHORS: Mathias J Gerl, Michal A Surma, Celine Fernandez, Olle Melander, Satu Männistö, Katja Borodulin, Aki S Havulinna, Veikko Salomaa, Elina Ikonen, Carlo V Cannistraci, Kai Simons

Shotgun lipidomics of human plasma provides hundreds of individual lipid measurements in a fast, reproducible, single assay, making it a useful quantitative method for biomarker identification. In this study we trained machine intelligence models to predict obesity estimates, i.e. body mass index (BMI), waist-hip ratio (WHR) and body fat percentage (BFP), on a lipidomic dataset of 1061 samples of the FINRISK 2012 cohort and confirmed the outcome by an independent validation dataset of the Malmö Diet and Cancer Cardiovascular Cohort. Comparison of the different models revealed that the lipidome predicted BFP the best. Moreover, the plasma lipidome also contains information about body fat distribution, since WHR was predicted more accurately than BMI. These modelling results required full resolution of the lipidome to lipid species level. The power of the lipidomics association was demonstrated by the finding that the addition of routine clinical laboratory variables, e.g. HDL- or LDL- cholesterol did not improve the model further. Correlation analyses of the individual lipid species, controlled for age and separated by sex, demonstrated the multi-parametric nature of the correlation with the BFP. Correlation profiles were similar between the three obesity estimates, but very different from those lipids correlating with HDL-, LDL-cholesterol, and triglyceride levels.
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P-121 Metabolite Trajectories Following Contrasting Prudent and Western Diets from Food Provisions: Identifying Biomarkers of Short-term Changes in Habitual Diet

PRESENTING AUTHOR: Philip Britz-McKibbin, McMaster University, Canada

CO-AUTHORS: Nadine Wellington, Meera Shanmuganathan, Russell J. de Souza, Sandi Azab, Mateen Sheikh, Michael Zulyniak, Jonathon Bloomfield, Alicia Mell, Ritchie Ly, Dipika Desai, Sonia S. Anand

Recent changes to habitual diet play important roles in population health, including alarming rises in obesity prevalence and chronic disease risk worldwide. However, few objective biomarkers of recent food intake are used in nutritional epidemiology, which rely on food frequency questionnaires or dietary records prone to bias and selective reporting. Herein, metabolomic analyses were performed on healthy participants (n=42) from the Diet and Genetic Intervention (DIGEST) study based on a parallel two-arm randomized clinical trial. Matching urine and plasma specimens were collected at baseline and following a 2-week assigned Prudent or Western diet, where participants were provided all food items with a weight-maintaining menu plan from a dietician. Targeted and non-targeted metabolite profiling was conducted using three complementary instrumental platforms with stringent quality control to avoid false discoveries. Metabolic phenotype changes were characterized based on distinctive trajectories following 2 weeks of food provisions as compared to baseline habitual diet of participants when using univariate and multivariate statistical models. Unknown metabolites associated with contrasting dietary patterns were identified with high resolution MS/MS and co-elution after spiking with authentic standards. Top-ranked metabolite trajectories were also correlated to self-reported changes in average intake of macro/micronutrients from diet records. For the first time, we have identified robust biomarkers sensitive to short-term changes in dietary patterns from food provisions that are applicable to a healthy and free-living population outside of a laboratory setting.

P-122 A step-wise nutrimetabolomics approach reveals food-specific compounds in urine of adults consuming a DASH-style diet

PRESENTING AUTHOR: Nichole Reisdorph, University of Colorado, United States

CO-AUTHORS: Nichole A. Reisdorph, Audrey E. Hendricks, Minghua Tang, Katrina A. Doenges, Richard M. Reisdorph, Brian C. Tooker, Kevin Quinn, Sarah J. Borengasser, Yasmeen Nkrumah-Elie, Daniel N. Frank, Wayne W. Campbell, Nancy F. Krebs

Although health benefits of the Dietary Approaches to Stop Hypertension (DASH) diet are established, it is not understood which specific compounds in foods are responsible for these benefits. We utilized a step-wise approach to identify unique compounds from individual foods of a DASH-style diet, determined if these food-specific compounds (FSCs) are detectable in urine, and then examined relationships between these urinary-FSCs and blood pressure (BP). Nineteen subjects were randomized into 6-week controlled DASH-style diet interventions. Untargeted, LC/ MS-based metabolomics was performed on 24-hour urine samples collected before and after each intervention and on 12 representative DASH- style foods. Linear mixed effects models were used to correlate FSCs to BP changes. Mass spectrometry signals for FSCs were summed to derive a food-specific signature to evaluate nutrikinetics. Between 66-969 compounds were determined to be FSCs and between 13-190 of these FSCs were detected in urine. Nutrikinetics demonstrated a relationship between food consumption and presence of food specific signatures in urine. Although no urinary FSCs were associated with BP, 16 and 6 non-FSC, urinary compounds were associated with BP and changes in BP over time, respectively. These comprised both endogenous and exogenous compounds, including some food-related compounds that were not analyzed by LC/MS/MS in this study. This study establishes a technical, analytical, and conceptual framework upon which future nutrimetabolomics studies can be built. A novel aspect of this study is the use of food-specific signatures to evaluate nutrikinetics.

P-123 Syringol metabolites as biomarkers of smoked meat intake

PRESENTING AUTHOR: Roland Wedekind, International Agency for Research on Cancer, France

CO-AUTHORS: Pekka Keski-Rahkonen, Nivonirina Robinot, Vivian Viallon, Pietro Ferrari, Erwan Engel, Marc J. Gunter, Inge Huybrechts, Augustin Scalbert

Background: Processed meat is associated with higher risk of colorectal cancer but the estimation of intake of this heterogeneous food group in epidemiological studies is challenging because of the lack of sufficient details in dietary questionnaires. Objective: To identify novel biomarkers of intake of processed meat products using metabolomics. Design: An untargeted metabolomic approach based on LC-MS was applied to processed meat products previously digested in vitro, and to urine and plasma samples from a randomized cross-over dietary intervention in which 12 volunteers consumed successively 3 processed meat products and two other control foods during 3 days. The identified biomarkers were then measured in urine from 474 subjects from the European Prospective Investigation into Cancer and nutrition (EPIC) cross-sectional study for which a 24h dietary recall and food frequency questionnaires were available. Results: Syringol and four derivatives of syringol were found to be characteristic of digests of smoked meat products. The same compounds present as sulfate esters in urine showed increased levels following consumption of smoked meat products in the intervention study. They were also positively associated with recent and habitual consumption of smoked meat products in urine samples from participants of the EPIC cross-sectional study. These markers showed good discriminative ability for smoked meat intake with receiver operator characteristic areas under the curve up to 0.86 and 0.79 for short-term and habitual intake, respectively. Conclusions: The biomarkers of smoked meat intake identified in this study may be used to improve assessment of smoked meat intake in epidemiological studies.
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P-124

Association of the metabolome with health parameters and food intake in a prostate cancer cohort; an untargeted
metabolomics study

PRESENTING AUTHOR: Johnny R Östman, Swedish University of Agricultural Sciences, Sweden

CO-AUTHORS: Rui C Pinto, Elin Thysell, Timothy MD Ebbels, Göran Hallmans, Ali A Moazzami

Prostate cancer (PCa) is the most frequently diagnosed cancer and the second most common cause of cancer-related death in men. The associations between PCa risk and pre-diagnostic metabolite levels have been previously investigated, but have yielded inconclusive results. We used a liquid chromatography-high resolution mass spectrometry untargeted metabolomics approach to look for metabolites associated with the risk of future PCa in fasting plasma using a nested case-control study design of 777 pairs of PCa cases and their matched controls (n = 1554) recruited from Northern Sweden Health and Disease Study Cohort (NSHDS). In order to avoid variation we only included cases with a follow-up of over 5 years. Within this cohort an additional sub-cohort of cases with aggressive PCa was identified (n = 169 pairs). A range of health parameters (i.a. body mass index, 2-hour oral glucose tolerance test, food frequency questionnaire answers) was collected for all subjects at baseline. The untargeted metabolomics approach identified approximately 3000 features, which were further condensed into approximately 1200 features using a novel batch matching algorithm. The associations of the metabolomic features with the health parameters were investigated using conditional logistic regression for both the whole dataset and the aggressive cancer sub-cohort. Indications of associations between hitherto unidentified metabolomic features and health parameters could be shown, shedding light on observable metabolic changes that might manifest as future PCa.

P-125

Comparison of Serum Non-Esterified and Total Fatty Acids as Reliable Biomarkers of Maternal Dietary Fat Intake:
A Pilot Study in the FAMILY Birth Cohort

PRESENTING AUTHOR: Sandi Azab, McMaster University, Canada

CO-AUTHORS: Russell DeSouza, Natalie Campbell, Michael Zulyniak, Sonia Anand, Koon Teo, Philip Britz-Mckibbin

Fatty acids (FAs) are dietary components that have long been implicated in health and disease. However, FAs analysis encompasses diverse fractions derived from blood, erythrocytes or adipose tissue. To date, serum phospholipid and total lipid fractions are often used in epidemiological and nutrition studies with a notable gap regarding the clinical utility of more convenient lipid pools for dietary biomarkers, such as serum non-esterified FAs (NEFA). In this study, 50 subjects from FAMILY birth cohort were selected based on a devised diet index to constitute a "good diet" and a "poor diet" group. Comprehensive analyses of serum NEFA and total FAs were performed using multisegment injection-non-aqueous-capillary electrophoresis-mass spectrometry (MSI-NACE-MS) to investigate associations of circulating FAs with the diet index score, fish, dairy and fiber servings derived from standardized food-frequency questionnaires (FFQs). Pregnant women within the good diet group had higher EPA and DHA (q < 0.05; FDR) in both analyzed fractions. These also showed significant correlations with reported omega-3 FAs servings notably non-esterified EPA (r = 0.46; p < 0.0001). Additionally, serum odd-chain FAs, such as non-esterified C15:0 demonstrated the highest correlation to full-fat dairy intake (r = 0.43; p < 0.001). For the first time, we demonstrate that direct analysis of serum NEFA using MSI-NACE-MS offers a high-throughput approach for reliable assessment of habitual fat intake that avoids complicated sample fractionation, hydrolysis, derivatization and long analysis times. These findings endorse the role of metabolomics for high-quality observational studies investigating the impact of maternal nutrition on birth outcomes.

P-126

Untargeted metabolomics to reveal red versus white meat-associated gut metabolites in a prudent and Western
dietary context

PRESENTING AUTHOR: Sophie Goethals, Ghent University, Laboratory of Chemical Analysis, Merelbeke, Belgium, Belgium

CO-AUTHORS: Sophie Goethals, Caroline Rombouts, Lieselot Y. Hemeryck, Lieven Van Meulebroek, Thomas Van Hecke, Els Vossen,
John Van Camp, Stefaan De Smet, Lynn Vanhaecke

The underlying mechanisms of the association between red and processed meat intake and a higher risk for a range of chronic diseases are not fully elucidated yet and can probably be affected by other dietary components. Untargeted metabolomics in the gut is a promising approach to investigate the response of host and microbiome on the consumption of meat in the context of dietary pattern. The impact of red and processed meat versus chicken combined with a prudent or Western dietary pattern on the gut metabolome was investigated by using a four week pig feeding trial as a model for humans. Thirty-two piglets received one of the four dietary treatments mimicking human diets. Untargeted ultra-high performance liquid chromatography coupled to high resolution mass spectrometry (UHPLC-HR-Q-Orbitrap-MS) (Vanden Bussche et al., 2015, Anal. Chem.), preprocessing with Compound DiscovererTM and multivariate statistics using Simca 14.1 and RStudio were applied to characterize the metabolic fingerprints of the pig small intestine and colon digests. The validated OPLS-DA models (R2X>0.35, R2Y>0.99, Q2>0.71 and p-values CV-ANOVA<0.005) investigating the effect of 'dietary pattern' and 'meat type' could demonstrate a higher impact of dietary pattern compared to meat type on the gut metabolome. The abundance of most meat-associated metabolites did not depend on the dietary pattern. However, some metabolites such as long-chain acylcarnitines were only present at high levels in the pigs fed the 'Western-Red&Processed' diet. In addition to the confirmation of previously described chicken and red meat-associated biomarkers (anserine, carnosine, carnitine,...), new interesting metabolites were tentatively identified.
<figure><img src="image_44.png" /></figure>

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P-127

The Age Metabolome: A Consortium of Metabolomics Studies (COMETS) Meta-analysis of 91,965 Adults

PRESENTING AUTHOR: Steven Moore, NCI, United States

CO-AUTHORS: Steven C. Moore, Ella Temprosa, Ewy Mathe, Krista Zanetti, Jessica Lasky-Su, Rachel S. Kelly

Age is the most important risk factor for human morbidity and mortality, but its specific metabolic effects are incompletely understood. To clarify the age-metabolism relationship, we evaluated correlations of age with levels of serum and plasma metabolites in 36 cohort studies and 91,965 adults in COMETS. Cohorts were from North America (N=15), Europe (N=13), and Asia (N=6) and the median age at blood collection was 55y (range:18-90y). Metabolomics data were generated predominantly by Metabolon (N=12 cohorts), the Broad Institute (N=7), Nightingale Health (N=7), or from Biocrates kits (N=6). We analyzed cohort-specific Spearman age-metabolite correlations, adjusted for sex, smoking, fasted status, BMI, race/ethnicity, and more. We meta-analyzed results for metabolites measured in at least 6 studies (random-effects). Overall, 1,136 metabolites were measured in at least 6 studies. Across these 1,136 metabolites, the median number of participants with measured values was 13,457, and the maximum was 91,965. In total, 290 metabolites were significantly correlated with age at the Bonferroni significance threshold (p<0.00004); 247 correlations were positive, 43 were inverse. The top 10 positive correlations were for neurotransmitter precursors and products, like vanillylmandelic acid (r=0.31;p=2.1*10-27) and C-glycosyltryptophan (r=0.29;p=2.1*10-13), and urea cycle metabolites like 2,3-dihydroxy-5-methylthio-4-pentenoate (r=0.29;p=2.1*10-13) and symmetric dimethylarginine (r=0.23;p=1.8*10-8). The top 10 inverse correlations were sex steroid hormones, e.g. dehydroepiandrosterone sulfate (r=-0.29;p=3.3*10-16). Associations replicated across cohorts, regions, platforms, sex, and BMI and smoking history groups. These findings highlight specific perturbations in metabolism of the central nervous system, the urea cycle, and steroid hormones are associated with older age. Findings were reproducible and generalizable.

P-129

Perfluoroalkyl substances, the plasma metabolome and risk of Type 2 Diabetes - a prospective nested case-control study
in a Swedish population

PRESENTING AUTHOR: Tessa Schillemans, Karolinska Institutet, Sweden

CO-AUTHORS: T. Schillemans, S. Lin, C. Donat-Vargas, A. Tornevi, M. Wennberg, J. Sommar, I. Johansson, J. Koponen, H. Kiviranta, K. Hanhineva, O. Rolandsson, I.A. Bergdahl, R. Landberg, A. Åkesson, C. Brunius

Perfluoroalkyl substances (PFAS) are widespread and persistent environmental pollutants. There is evidence that PFAS induce metabolic perturbations, but underlying mechanisms are still unknown. We used untargeted LCMS metabolomics (n=24758 features) to find metabolites related to PFAS exposure in a case-control study on type 2 diabetes (T2D) (n=187 matched pairs) nested within the Västerbotten Intervention Programme cohort. Exposures of six measurable PFAS, were grouped into two patterns by principal component analysis: 1) perfluoronanoic acid, perfluorodecanoic acid and perfluoroundecanoic acid and 2) perfluorooctane sulfonic acid, perfluorooctanoic acid and perfluorohexane sulfonic acid. Using a random forest algorithm, we discovered metabolite features associated with individual PFAS or PFAS exposure patterns, which were subsequently investigated for associations with risk of T2D. PFAS exposures correlated with 154 features (0.15 ≤ IrI ≤ 0.35) after adjustment for gender, age, sample year and case-control status. Two PFAS-related features also associated with T2D after adjustment for matching factors (gender, age, sample year) and for fish and meat intake, but not for BMI. These metabolites, putatively identified as a phosphatidylcholine and a diacylglycerol, had opposite directions of associations with PFAS exposures and T2D risk: The phosphatidylcholine correlated positively with perfluorodecanoic acid (r=0.22) and associated inversely with risk for T2D (OR=0.35; 99.9% CI=0.16-0.79), the diacylglycerol correlated negatively with perfluorodecanoic acid (r=-0.18) and associated directly with risk for T2D (OR=1.93; 99.9% CI=1.02-3.65). Our results suggest that especially perfluorodecanoic acid-related metabolites may have inverse associations with T2D risk.
<figure><img src="image_45.png" /></figure>

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Human Metabolome Technologies
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P-130 Untargeted metabolomics profiling of longitudinal urine samples to determine the personalized baseline for integrated
personalized omics profiling (iPOP) project

PRESENTING AUTHOR: Songjie Chen, Stanford University, United States

CO-AUTHORS: Yuqin Dai, Liang Liang, Michael Snyder

iPOP project aims at defining personalized health baseline by multi-omics profiling of diverse longitudinal samples collected from individual participants. The easy accessibility and noninvasive sampling of urine make it promising for longitudinal metabolomics analysis. However, such analyses remain challenging due to complexity and broad dynamic range of metabolites. We developed a robust high performance HILIC Q-TOF LC/ MS method to profile urine samples with broad coverage of metabolite classes, analytical selectivity and reproducibility despite high sample salt concentration. The method was validated by consistent measurement of a pooled quality control urine sample and further applied to profile samples of an iPOPer with a high sampling frequency. The untargeted metabolomics analysis of a pooled quality control sample found more than 3700 metabolic features. The preliminary results showed reproducible retention time and signal response for 500 sample injections over a one-week of LC/MS data acquisition time. A panel of highly sensitive hydrophilic metabolites such as sugar phosphates and nucleotides were detected with an enhanced signal response by incorporating medronic acid additive. This is the first case in iPOP project to discover the longitudinal personalized urine phenotype by consistent metabolomics profiling.

P-131 Targeted urine metabolomics using UPLC-QTOF-MS combined with a reporting tool is a high throughput screening for IEM

PRESENTING AUTHOR: Irene Körver-Keularts, Clinical Genetics, MUMC+, Netherlands

CO-AUTHORS: Steinbusch L K M, Wang P, Waterval W A H, Stassen F, Bierau J, Habets D D J

BACKGROUND: In an effort to consolidate several dedicated biochemical urine tests and shorten our turn-around-time we developed an innovative targeted urine metabolomics screening containing 226 biomarkers covering 242 OMIM phenotypes and a reporting tool to facilitate diagnosis. METHODS: Creatinine normalized urine samples were spiked with three internal standards (IS) (13C6-galactitol, D4-sebacic acid and D3-hexanoylglycine) and run on a UPLC-QTOF-MS in positive and negative modes. Acquired untargeted data were extracted for the relative signal over IS of targeted analytes in both 10 and 50 ppm mass extraction windows. Peak overloading was automatically corrected and peak shifting and peak quality were notified. Z-score of each analyte was calculated against an age-matched control cohort of 280 samples. Disease phenotypes were based on scores from biomarker matching. Needle plots visualised all abnormal analytes and a heatmap showing the predicted disease phenotypes. RESULTS: 298 unique samples from 273 patients covering 75 OMIM phenotypes were analyzed in our clinical validation. We were able to correctly diagnose, amongst others, organic acidurias and defects in amino acids, purines and pyrimidines and vitamin and cofactors metabolism. Some IEM, eg. sterol and peroxisomal metabolism, need further evaluation in targeted plasma metabolomics. This innovative method reduced the turn-around-time significantly. DISCUSSION: In conclusion, we developed a fast targeted urine metabolomics tool which replaces a number of dedicated urine analyses for efficient screening of patients suspected of an IEM.

P-132 Designing a new class of covalent QS inhibitors to target P. aeruginosa virulence

PRESENTING AUTHOR: Shaked Uzi, Student, Israel

Bacteria have the ability to communicate with each other and sense their population densities through secretion of small signaling molecules called autoinducers, in a process that is known as 'quorum sensing' (QS). These days, the increasing prevalence of antibiotic resistance constitutes a worldwide problem and targeting bacteria through QS inhibition may provide a sophisticated new strategy to engage this issue. P. aeruginosa is an opportunistic pathogen which regulates its pathogenicity through QS. Its main autoinducer, 3-oxo-C12-homoserine lactone (C12), binds to the LasR transcriptional regulator protein and activates a cascade of events that regulates biofilm formation and secretion of virulence factors. By targeting covalently the Cys79 residue inside the LasR binding pocket, irreversible inhibition of the QS in P. aeruginosa can be achieved. In this project, a covalent inhibitors containing Michael acceptors with different chain lengths were designed and their bio-activity was examined. Two of the designed probes were found to bind covalently to LasR but surprisingly none of them were able to reduce pyocyanin production, a hallmark of Pseudomonas virulence. On the other hand, even though some of these probes were partial agonists, they still were able to reduce the bacterial virulence and damage its ability to form biofilms.
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P-133

Towards state-of-the-art in TB Meningitis metabolomics diagnostics

PRESENTING AUTHOR: Shayne Mason, Centre for Human Metabolomics, North-West University, South Africa

The infectious agent (M. tuberculosis) responsible for TB can spread to the brain; inflammation of the meninges leads to TB meningitis (TBM). Diagnosis requires clinical, chemical, microbiological and PCR analysis of cerebrospinal fluid (CSF) — the diagnostic gold standard, but unfortunately sometimes inconclusive. A missed/delayed diagnosis staggers correct treatment, leading to severe neurological morbidities, or even death, especially in paediatrics. Through metabolomics, we developed a defining biochemical profile of neuroinflammation that, in time, will become a differential diagnostic point-of-care method for TBM. Based on untargeted 1H-NMR metabolomics on CSF, we proposed the astrocyte-microglia lactate shuttle for TBM, which gained increased recognition following our experimental support through LC-MS and amino acid profiling results. We're currently exploring CSF metabolomics of TBM and other forms of meningitis, aimed at validating a differential CSF diagnostic profile for TBM. Urinary GC-MS metabolomics holds promise for a non-invasive method of diagnosis and prognosis for TBM, complemented with our studies and across other types of infectious diseases (e.g. HIV), which alert to commonalities within the gut-liver-brain axis. Advanced metabolomics technology (GCxGC-TOF-MS) will serve to further characterize neuroinflammatory markers in the urine. Finally, we believe CSF metabolomics using a new ionic profiling method assessing changes of ion-channels and transporters within the brain will open a state-of-the-art diagnostic approach to neuroinflammation. With our established metabolomics expertise (50% of outputs on TBM metabolomics), combined with other omics data, a defined biochemical profile of neuroinflammation seems to be in the offering — an enterprise for which international collaboration would be indispensable.

P-134

The Immunomodulatory Effect of Propolis in THP-1 Derived Macrophages and in Primary Macrophages

PRESENTING AUTHOR: David Watson, University of Strathclyde, United Kingdom

CO-AUTHORS: Abdulmalik Alqarni, Samyah Alanazi, Naif D. Alenzi, Samya Alenezi, James Fearnley, Hugo Fearnley, Valerie A. Ferro, William Harnett

Propolis is collected by bees from the plants in the environment around their hives and its composition varies according to the available plants. In temperate regions it is largely collected from poplar buds. It is used to coat hive surfaces as an anti-infective being particularly active against protozoal species. It is a complex mixture and it has multiple biological effects. In the current study propolis extracts from different geographic origins were assessed for their anti-inflammatory activities by investigating their ability to alter the production of tumour necrosis factor-α (TNF-α) and cytokines in THP-1 derived macrophage cells (THPMs) co-stimulated with lipopolysaccharide (LPS) and in primary macrophages stimulated with LPS. In the THPMs the propolis extracts suppressed the levels of TNF-α and IL-6 cytokines produced by LPS-stimulation. Similar suppression effects were detected for IL-1β, but the release of this cytokine was synergised by propolis samples from Ghana and Indonesia when compared with LPS. Overall, a Cameroonian propolis extract (P-C) was the most immunosuppressive and this was evaluated for its effects on the metabolic profile of unstimulated macrophages or macrophages activated by LPS. Metabolites were identified by liquid chromatography coupled with mass spectrometry. LPS altered energy, amino acid and nucleotide metabolism in THP-1 cells. A very specific effect of the P-C propolis appeared to be the inhibition of purine nucleotide phosphorylase. Extracts of propolis from Brazil and the UK were found to inhibit the immune response in primary murine macrophages and in this case the target appeared to be nitric oxide production.

P-135

Investigating Canine Hepatocutaneous Syndrome Through an Untargeted Metabolomic Approach

PRESENTING AUTHOR: M. Elena Diaz-Rubio, Cornell University, United States

CO-AUTHORS: Adam J. Miller, John P. Loftus, Luis P. Macho, Sharon A. Center, Sheng Zhang

Hepatocutaneous Syndrome (HCS) is a canine disease characterized by a distinct hepatopathy and cutaneous lesions in conjunction with hypoaminoacidemia. Aminoaciduria has been recently identified as component of this syndrome and lysinuria specifically has been identified as a consistent feature of this syndrome. Many HCS associated metabolic abnormalities may relate to altered amino acid metabolism. However, comprehensive links between changes in amino acid concentrations other metabolic alterations remain unresolved. Therefore, an untargeted metabolomics approach analyzed plasma from dogs with HCS and compared them to healthy dogs of similar ages and breeds to further characterize this disease. Plasma from dogs with HCS (n=19) and healthy control dogs (n=9) were analyzed. Chromatographic separation was performed using Hilic method on a Vanquish UHPLC coupled to a QE-HF mass spectrometer. All samples along with the QCs were run in negative and positive ion modes and the acquired data were processed using Compound Discoverer 3.0. Metabolites were identified with Compound Discoverer 3.0 software through the mzCloud HRAM fragmentation library. Statistical Analyses were performed with Metaboanalyst 4.0 and SIMCAP + software (Umetrics, Sweden). Preliminary results identified significant differences (P < 0.01) between HCS and healthy dogs in a variety of metabolites. These metabolites are involved in pathways that include vitamin B6 metabolism, the citric acid cycle, pyrimidine metabolism, pantothenate and CoA synthesis, and various amino acid metabolic systems. These results begin an in-depth analysis of metabolic perturbations that define HCS. We have identified metabolites as candidate biomarkers and novel treatments target for HCS.
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P-136 Metabolomic Investigation of Immune Cell Activation

PRESENTING AUTHOR: Florence A. Castelli, CEA: French Alternative Energies and Atomic Energy Commission, France

CO-AUTHORS: Amir Louarr, Aurélie Delvaux, Patricia Lamourette, Emeline Chu-Van, Evelyne Correia, Bernard Maillere, Christophe Junot, François Fenaille, Florence Anne Castelli

In recent years, it has been shown that some specific metabolites could be involved in immune cell polarization during infection, thus shaping the immune response. Within the adaptive immune system, dendritic cells (DCs) play a central role, orienting the immune response according to the perceived danger signal. While metabolism seems to significantly impact DC activation, the underlying mechanisms are still poorly described and understood. We aimed to develop a comprehensive method to get deeper insight into DC metabolic reprogramming. Monocyte-derived dendritic cells were in vitro activated either with lipopolysaccharide (LPS, bacterial signal) or poly:IC (viral signal) and their corresponding metabolic responses studied by an untargeted LC/HRMS-based metabolomics approach. Statistical data analyses were used for thoroughly assessing specific metabolic differences. We described the first comprehensive metabolic map of DCs (> 150 metabolites robustly monitored) and identified dramatic metabolic changes upon DC activation with LPS (>100 metabolites impacted), whereas bacterial and viral DC activations can be distinguished by significant fluctuations in more than 70 metabolites. Those Metabolomic analyses revealed alterations in four main metabolic pathways (alanine-aspartate-glutamine, glutathione, and pyrimidine pathways, Krebs cycle), significantly upregulated upon bacterial infection and downregulated in the case of viral infection. The few metabolites already described were confirmed while many others were also highlighted, thus enabling a better comprehension of the metabolic mechanisms of pathogen-specific DC activation. Our approach represents an unprecedented, powerful and straightforward way to robustly monitor metabolic activation of immune cells that would facilitate the discovery of biomarkers specifically signing bacterial or viral infection.

P-137 Discovering metabolic biomarkers for predicting efficacy of anti-histamine treatment in chronic urticaria patients

PRESENTING AUTHOR: SiHyun Chae, Seoul National University, School of Medicine, South Korea

CO-AUTHORS: Da Jung Kim, Andrew HyoungJin Kim, Min-Gyu Kang, Joo-Youn Cho

Chronic urticaria is a chronic inflammatory skin disease that occurs for more than six weeks and recurs frequently. First line treatment of chronic urticaria is anti-histamine, which is proven to be effective but bares large inter-individual variation in response. Thus, the aim of this study was to discover metabolic biomarkers for predicting therapeutic outcome of anti-histamine treatment in patients with chronic urticaria by using metabolomics approach. Total 60 plasma samples were collected from patients suffering from chronic urticaria. Twenty five of them showed response to anti-histamine and thirty five of them were diagnosed as non-responders. Plasma metabolomes were analyzed using GC-TOF-MS. Multivariate statistical analysis were conducted where biomarkers were selected according to fold change difference between two groups with false discovery rate adjusted P value less than 0.05. As a result, palmitic acid and stearic acid were selected as putative biomarkers, which were significantly higher in non-responder group. Therefore, we speculate changes in lipid metabolism are linked with the efficacy of anti-histamine treatment in chronic urticaria and by understanding the mechanism, the therapeutic outcome of anti-histamine treatment in chronic urticaria patients can be predicted.

P-138 Metabolomics as a tool to discover metabolite biomarkers for cow milk allergy diagnosis

PRESENTING AUTHOR: Lynn Vanhaecke, Ghent University, Belgium

CO-AUTHORS: Ellen De Paepe, Lieven Van Meulebroek, Eric Cox

In industrialized nations, food allergies are a growing epidemic and are considered a major thread to our wellbeing. Cow milk allergy is one of the first allergies to occur in early childhood and early life sensitization has been associated with an increased risk to develop the atopic march, including eczema, asthma and other food allergies later in life. As such, more research is urgently needed to gain more insights into this disease. Therefore, this study evaluated a unique multi-matrix platform for polar metabolic fingerprinting of feces, plasma and urine, applying UHPLC-Q-OrbitrapTM-HRMS, to determine the optimal matrix for future research on cow milk allergy in children. Plasma is popular for metabolomic analysis, but collection is problematic in young children, while feces and urine are readily available biofluids. All three fingerprinting approaches were proven 'fit-for-purpose' through extensive validation in which excellent linearity (R2 > 0.99 or 0.90 respectively), recovery and precision (coefficient of variance < 15% or 30% respectively) were observed. The effectivity of the platform was demonstrated by subjecting simultaneously collected fecal, urine and plasma samples from 10 healthy volunteers to metabolic profiling and fingerprinting, yielding respectively 9672, 9647, and 6122 components, with a substantial overlap of the plasma metabolome with fecal (69.48%) and urinary samples (76.79%). Orthogonal partial least-squares discriminant analysis provided similar results for feces and plasma in gender-discrimination (p-value = 0.036), suggesting feces as a promising alternative biofluid to plasma for food allergy research. The latter was confirmed by highly promising results in preliminary experiments.
<figure><img src="image_48.png" /></figure>

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P-139

Metabolic perturbations in response to enteropathogen infections in children from resource constrained settings

PRESENTING AUTHOR: Natasa Giallourou, Integrative Systems Medicine and Digestive Diseases, Department of Surgery and Cancer, United Kingdom

CO-AUTHORS: Fahmina Fardus-Reid, Gordana Panic, Eric Houpt, Margaret Kosek, Jonathan Swann

Early-life enteropathogen infections are major drivers of diarrhoea and stunted growth in children living in under-resourced settings. Infections and malnutrition continue to impact the growth and development of millions of children worldwide, despite a variety of anti-microbial, nutritional and hygiene interventions as well as improved access to vaccination programs. Untargeted 1H NMR spectroscopy was used to characterize the metabolic profile of urine samples collected longitudinally from children from Peru (n=273 infants, N=1057 samples), Tanzania (n=249 infants, N=506 samples) and Bangladesh (n=249 infants, N=860 samples) in the first two years of life, participating in the multisite birth cohort study (MAL-ED). We estimated associations between metabolomic data and data obtained from quantitative PCR used to detect 29 enteropathogens in stools collected from the same cohorts. Shifts in gut microbial metabolites arising from the catabolism of amino acids like tyrosine, tryptophan and phenylalanine were associated with pathogens like Giardia, Norovirus, Campylobacter and Escherichia coli pathotypes. Additionally, energy expenditure appears to be modified in infected children reflected in shifts of nicotinamide metabolism. Urinary lactose levels were positively associated with viral infections suggesting increased intestinal permeability in infected children. The majority of infection-related metabolic shifts were also observed in children with poor growth outcomes. This work has generated new insights into the biochemical perturbations of enteric infections in infants from developing countries, providing a metabolic framework from which nutritional programs and interventions for environmental enteric dysfunction can be more precisely constructed and evaluated.

P-141

Superbug Surveillance

PRESENTING AUTHOR: Soren Wacker, University of Calgary, Canada

CO-AUTHORS: Ian Lewis, Sergei Y. Noskov, Annegret Ulke-Lemee, Thomas Rydzak, Yonatan Grad, Deirdre Church, Fiona Clement, Ashlee Earl, Christopher Naugler, Rauf Salamzade

The rise of antibiotic-resistant bacteria is a problem so serious that it threatens modern medicine around the globe. Half of the common bacteria are already resistant to front-line drugs. New extremely resistant microbes are already emerging which cannot be cured with conventional drugs anymore. Calgary Laboratory Services (CLS) has collected bacteria from the population of Calgary ("1 million people) within the past 20 years, including every single strain cultured from bloodstream infections. At the University of Calgary, these bacteria are re-grown and dismantled with a multi-omics approach (metabolomics, proteomics, genomics) to understand the spread and the origins of multi-drug resistance, in the worldwide largest population-based study addressing infectious diseases.

P-142

The mode of action of T. gondii tissue cyst inhibitors

PRESENTING AUTHOR: Deborah Maus, Robert Koch-Institute, Junior Group 2, Berlin, Germany, Germany

CO-AUTHORS: Jens Pikkemaat, Elyzana Dewi Putrianti, Martin Blume

The intracellular, apicomplexan parasite Toxoplasma gondii infects up to 30% of the global human population and causes life-threatening diseases in immuno-compromised patients. Chronically persisting bradyzoites form cysts in brain and muscle tissues and are responsible for transmission and remission of this disease. However, currently available medical treatment options are only effective against the virulent tachyzoites but fail to target the chronic stages of T. gondii. To address this shortcoming, we are screening antimicrobial compound libraries against both stages of the parasite in a fluorescence-based assay in a plate format. To identify the molecular target of inhibitory compounds we pursue an untargeted metabolomics approach using HILIC-UHPLC-MS: The metabolic fingerprint of treated parasites will be compared with the impact of characterized inhibitors with known modes of action. In subsequent reverse-genetic, knock-down und fluxomics experiments we will further characterize the potential T. gondii cyst inhibitor and its molecular target.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

BIOMEDICAL

P-143

Taking the metabolomic approach to look at multiple organ dysfunction syndrome (MODS) in trauma patients

PRESENTING AUTHOR: Anna Karen Laserna, National University of Singapore, Singapore

CO-AUTHORS: Jorming Goh, Lynette Loo, Jialing Neo, Pavandip Singh Wasan, Mikael Hartmann, Mahesh Uttamchandani, Philip Iau, Sam Fong Yau Li, Shabbir Moochhala

The developments in trauma care have led to a decrease in immediate and early mortality among trauma patients. However, with the decrease in early trauma mortality, a new cause of death in the intensive or post-operative care units was found, wherein patients succumb to complications in organs unrelated to the initial injury. It is called multiple organ dysfunction syndrome (MODS), which was defined as a condition of altered organ function in which an acutely ill patient cannot be maintained in homeostasis unless provided with medical intervention. This arises as a consequence of an overwhelming systemic inflammatory response. In this pilot study, we take a metabolomic approach to assess the development of MODS in relation to the metabolic perturbations of patients through time and try to identify the association of metabolites with organ-specific or multiple organ dysfunction. The study was done with 23 trauma patients admitted to the surgical intensive care and high dependency units having different degrees of injury severity at admission. Plasma samples were collected within the first 12 hours of inclusion in the study and every 12 hours thereafter until the 48th hour. Patient condition was evaluated using the sequential organ failure assessment (SOFA) scoring system. Untargeted metabolomic analyses were performed using reverse phase and hydrophilic interaction LC-MS. Multivariate analysis revealed that the metabolomic profile can be used to establish a total SOFA score threshold to distinguish MODS and non-MODS patients. Certain metabolites were also found to have significant correlation with MODS and organ-specific dysfunction.

P-144

Effects of PHMG, a humidifier disinfectant, on eye-dryness using LC-MS-based metabolite profiling

PRESENTING AUTHOR: Hyang Yeon Kim, Dankook University, South Korea

CO-AUTHORS: Jung Dae Lee, Jueng Eun Im, Soo bean Oh, Hyeyoon Goo, Kyong Jin Cho, Kyu-Bong Kim

Eye-dryness is multifactorial disease on eye and caused by many reasons such as contaminated external environment and use of systemic medications. In Korea, people who used humidifier disinfectant contained polyhexamethylene guanidine (PHMG) appealed discomfort in their eye. To investigate if PHMG worsens eye-dryness syndrome, we instilled PHMG solution (0.1% or 1%) to eyeball of rat, which was induced eye-dryness by scopolamine (3mg/kg for 7days). In this study, we used benzalkonium chloride (BAC), which is known as inducer of eye-dryness of positive control (PC). After application of PHMG for 5 days, the changes of tear production, break up tears film (BUT), corneal damage, number of lacrimal gland neutrophil and conjunctiva goblet cell were observed. The tear production, corneal damage, number of lacrimal gland neutrophil and detached cornea epithelium cells were increased in eye-dryness group compared with control group, while BUT and number of conjunctiva goblet cell were decreased. In addition, IL-6, IL-1β and TNF-α in cornea and gland were also significantly changed. Almost immune markers were increased in eye-dryness groups compared with control group. Analysis of PHMG effect on eye-dryness using liquid chromatography and mass spectrometry (LC-MS) were performed on plasma samples using SIMCA software. In partial least squares-discriminant analysis (PLS-DA), the clustering of control was clearly separated from eye-dryness, PC and PHMG groups. Moreover, eye-dryness group was differed from PHMG and PC groups. Some organic acid and lysoPCs and 10 non-identified compounds were selected as biomarkers of eye-dryness and deterioration of the symptom based on variable important plot (> 1.0).

P-145

Investigation of Plasmodium falciparum metabolome by UHPLC-ESI-HRMS: case study of two chemoresistant strains

PRESENTING AUTHOR: Denis Desoubzdanne, French Armed Forces Biomedical Research Institute (IRBA), France

CO-AUTHORS: Laura Desnouveaux, Jérôme Dormoi, Nicolas Taudon

Malaria is still one of the most widespread parasitic tropical diseases. Moreover, parasitic chemoresistance towards different antimalarial drugs is still expanding, whereas the biochemical mechanisms of its agent are so far poorly understood. In this context, we have proposed to investigate intra-parasitic metabolome of two Plasmodium falciparum strains by UHPLC-ESI-HRMS approach. The parasites were synchronized in schizonte stage after a Sorbitol treatment and a magnetic field separation (VarioMACS™ Separator, Miltenyi Biotec). In one hand, the African Mefloquine resistant strain 3D7 was exposed to the active drug Chloroquine at three doses (0x, 0.5x and 1xIC50 for 3 h. In the other hand, the Asiatic Chloroquine resistant strain W9 was exposed to the active drug Mefloquine at two doses (0x and 1xIC50) for 3 h. Parasites were isolated to the red blood cells with a Saponine treatment and washed with PBS. Intra-parasitic metabolites were extracted by microwaves in cold MeOH. After phospholipids + proteins depletion and evaporation to dryness, metabolites were re-suspended in acidified water/MeOH. They were separated with a Kinetex® Biphenyl LC column (Phenomenex) and then analyzed in both ESI+ and ESI- modes with an UHPLC-ESI-HRMS instrument (1290-6550A QTOF, Agilent). Metabolomics data were processing and normalized thanks to the open-source web-based W4M platform developed by the French metabolomics community (Giacomoni F. et al., 2014). Multivariate biostatistical analyses (PLS-DA, ANOVA) were realized in order to highlight putative signals correlated to the strain and/or the dose effects.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

BIOMEDICAL

P-146

Integrative analysis of in vivo host-parasite Metabolome, Genome and Transcriptome in malarial African children

PRESENTING AUTHOR: Wael Abdrabou, New York University, United Arab Emirates

CO-AUTHORS: Mame Massar Dieng, Aïssatou Diawara, Aboubacar S. Coulibaly, Amidou Diarra, Vinu Manikandan, Alfred B. Tiono, Sodiomon Sirima, Issiaka Soulama and Youssef Idaghdour

Plasmodium falciparum (Pf) malaria stands as one the most serious threats to global public health placing almost half of the world population at risk of infection. Symptoms of Pf malaria appear during the intra-erythrocytic developmental stage of the parasite when infected Red Blood Cells rupture releasing more parasites into the blood. However, host response to the infection can vary dramatically between individuals and between different ethnic groups through poorly understood mechanisms. During blood stage, P. falciparum engages with host in metabolites exchange and triggers de novo biogenesis pathways to ensure steady supply of nutrients needed for parasite proliferation. In this research project, we conduct a longitudinal matched in vivo study that aims at describing metabolic perturbations in sub-Saharan African children during Pf malaria and investigating if and how metabolites could modulate host response to infection. Our results reveal distinct metabolic processes and biochemical signatures in the serum samples of the infected children compared to their metabolomic profiles prior to infection. The overall goal of the study is to investigate metabolic profiles, and associated genotypic variants and gene expression traits using an integrative multi-omics approach. Achieving this goal will advance our understanding of the sources of variation in the host-parasite interactions taking place during malaria infection and provide a more holistic and systemic view to the biochemical-gene networks associated with the infection.

P-147

Metabolic Response to Supplemental Carnitine Identifies a Distinct Septic Shock Phenotype of Early Mortality

PRESENTING AUTHOR: Kathleen Stringer, University of Michigan College of Pharmacy, United States

CO-AUTHORS: Michael Puskarich, Charles Evans, Alla Karnovsky, Alan Jones

Background: Metabolic phenotyping of sepsis is challenged by patient heterogeneity. To better understand the metabolic derangements associated with early (28d) sepsis mortality, we are using metabolomics data from septic shock patients treated with supplemental L-carnitine. Methods: Temporal serum metabolomics data from non-survivors and survivors enrolled in the carnitine dose-ranging phase of a clinical trial (NCT01665092) were compared. P values were corrected for false discovery (FDR). Results: At T0, non-survivors (n=9), had higher median levels of measured acylcarnitines and a higher median C2:carnitine ratio (FDR<10%) versus survivors (n=12). Non-survivors also had T0 elevations in proline, histidine, and oleic acid (18:n-9) (FDR<15%). Carnitine (6, 12, 18 g) supplementation resulted in a non-dose dependent increase in median peak (T24) carnitine concentration (IQR) which was higher in non-survivors (562, 350-1132µM) versus survivors (222, 159-512µM; FDR=16%). Acyl-carnitines and C2:carnitine ratio remained elevated in non-survivors. Post-carnitine levels of proline and histidine declined in non-survivors but oleic acid remained elevated and stearic acid (18:0) progressively increased (FDR=16%). Demographic and clinical data (age, total SOFA, lactate and BMI) were not different between groups. Median (IQR) T0 renal SOFA was higher in non-survivors (1.0 [0-1] v. 2.0 [1-2.5], p=0.04) but there was no association between it and peak carnitine. Conclusion: Carnitine-treated non-survivors have evidence of disrupted carnitine metabolism prior to treatment that may contribute to elevated carnitine and acyl-carnitine levels in response to carnitine supplementation. These patients also have an inflammatory metabolic profile that may preclude their therapeutic responsiveness to carnitine and contribute to their mortality.

P-148

Elevated plasma and urine biomarkers for active Onchocerca volvulus infections

PRESENTING AUTHOR: Rob Vreeken, Janssen R&D, Belgium

CO-AUTHORS: Ole Lagatie, Emmanuel Njumbe Ediage, Dirk Van Roosbroeck, Stijn van Asten, Ann verheyen, Bieke Van Dorst, Linda Batsa Debrah, Alex Debrah, Ruben T'Kindt, Koen Sandra, Lieve Dillen, Filip Cuyckens and Lieven Stuyver1

The neglected tropical disease Oncocherciasis, or River Blindness, is caused by an infection with the filarial nematode Onchocerca volvulus. Approximately 17 million people, majority living in Africa, are infected world-wide. Until today there is neither a cure or a non-invasive diagnostic test available. Next, to enable PKPD studies with novel microfilaricide drug candidates, surrogate end-points and efficacy biomarkers are in high demand but non-existent. Here we report on the use of multimodal untargeted mass-spectrometry based biomarker discovery to identify onchocerciasis-associated metabolites and lipids in urine and plasma (O.volvulus infected cases: 68 individuals with palpable nodules; lymphatic filariasis cases: 8 individuals; non-endemic controls: 20 individuals). We identified 2 plasma metabolites, viz. inosine and hypoxanthine linked to filarial infection and one urine metabolite, i.e. cis-cinnamoylglycine, related to O. volvulus infection. Markers were confirmed (sensitivity, specificity) during a separate targeted validation experiment, using UPLC-HR-MS and UPLC-HR-MS/MS analysis. Next steps will focus on the application of these markers in microfilaricide clinical trials, MDA efficacy surveys and epidemiological transmission studies.
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**Editor-in-Chief**

Prof. Dr. Peter Meikle
Metabolomics Laboratory NHMRC,
Baker Heart and Diabetes Institute,
Melbourne, Victoria 3004, Australia

*Metabolites* (ISSN 2218-1989) is an international, peer-reviewed open access journal of metabolism and metabolomics, published monthly online by MDPI. *Metabolites* publishes original research articles and review articles in all molecular aspects of metabolism relevant to the fields of metabolomics, metabolic biochemistry, computational and systems biology, and biotechnology and medicine, etc. Its first Impact Factor will come out in June 2019.

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