## SESSION 18: FOOD APPLICATIONS 2

Wednesday, June 26

1:30 p.m. – 3:15 p.m.

**18A Session Keynote**
1:30 p.m. – 2:00 p.m.

Rapid Evaporative Ionisation Mass Spectrometry for detecting compounds related to consumer liking of meat

**PRESENTING AUTHOR:** Alastair Ross, AgResearch, New Zealand

**CO- AUTHORS:** Paul Middlewood, Stefan Clerens, Patricia L Johnson, Arvind Subbaraj, Patrick Silcock, Graham T Eyres, Carolina E Realini

Unbiased measurement of chemical components related to consumer liking is important for continuous improvement of breeding and meat processing for higher eating quality meat products, yet tools available for this purpose are limited. Rapid Evaporative Ionisation Mass Spectrometry (REIMS) is a mass spectrometry interface initially developed for surgery that allows real time analysis of samples, and is especially well suited for rapid analysis of meat. We hypothesised that within the metabolic signature of meat obtained using REIMS, it would be possible to detect compounds related to consumer liking. In a pilot study, 150 lambs were randomly selected within 10 different commercial mobs (n=15/group), and a 2 x 2 x 1 cm loin sample (Longissimus lumborum) collected for REIMS analysis. REIMS analysis was carried out in triplicate on 149 available samples in both positive and negative ionisation modes during two days. Associations between consumer panel (n=160 panellists) data and REIMS fingerprints were performed using PLS and OPLS-DA modelling, and confirmed using Pearson correlation (overall correlations) and ANOVA (between group differences). Meat with the highest overall liking scores was higher in compounds that are associated with aromatic amino acid biosynthesis and breakdown, while meat with lower overall liking scores was associated with a higher proportion of phospholipids. Using REIMS it was possible to detect compounds that were related to consumer liking of meat. In the future, this approach could be used to complement grading systems for identifying and predicting meat cuts with characteristics that maximize eating quality, and aiding consumer-driven breeding programmes.

**18B 2:00 p.m. – 2:20 p.m.**

Fiber mix supplementation in wheat-based flatbreads delays the exogenous appearance of glucose and its downstream metabolites

**PRESENTING AUTHOR:** Lisa Schlicker, BRICS, TU Braunschweig, Germany

**CO- AUTHORS:** Lisa Schlicker, Hanny M. Boers, Christian-Alexander Dudek, Gang Zhao, Jean-Pierre Trezzi, Doris M. Jacobs and Karsten Hiller

In nutritional intervention studies, the use of fully isotopically enriched plant material instead of single compound tracers enables deep insights into the postprandial catabolism of plant components (e.g. starch or protein). Due to its limited availability, only marginal amounts can be included in these studies, resulting in labeled plasma metabolites with 13C enrichment below natural enrichment of 1.1%, thus accurate quantification is analytically challenging. In a first step, we therefore developed an optimized mass spectrometry-based analytical workflow to achieve accurate quantification of 13C-enrichment in selected plasma metabolites below 1%. In a second step, we applied our workflow to plasma samples of a nutritional intervention study investigating the postprandial effects of fiber supplementation in wheat-based flatbreads. In this cross-over study, 12 healthy male subjects consumed flatbreads of different compositions: wheat flour (control) and wheat flour supplemented with 15% chickpea flour and different amounts of guar gum (2%: GG2, 4% GG4). We obtained time-resolved 13C enrichment profiles of 12 plasma metabolites namely glucose, lactate, alanine, glycine, serine, citrate, glutamate, glutamine, valine, isoleucine, tyrosine and threonine. While the postprandial metabolome was only mildly affected, fiber mix supplementation had a significant impact on the postprandial appearance of food-derived metabolites in the blood. Most interestingly, we found that fiber supplementation not only decreased the exogenous appearance of glucose. In addition, the appearance of the glucose-derived metabolites lactate and alanine was significantly reduced. The obtained data demonstrate the limitations of metabolite profiling and highlight that in vivo labeling contributes to a better understanding of nutritional interventions.

**18C 2:20 p.m. – 2:35 p.m.**

A metabolomic approach to the identification and validation of biomarkers of apple intake

**PRESENTING AUTHOR:** Aoife McNamara, Institute of Food and Health, Ireland

**CO- AUTHORS:** Helena Gibbons, Diana Gonzalez-Pena, Breige McNulty, Lorraine Brennan

The potential of individual food-intake biomarkers to objectively measure diet is a research area of interest. Improvements in dietary assessment are necessary to elucidate diet/health associations. The objective of this study was to identify novel biomarkers of apple intake and explore their potential to determine intake. Twenty volunteers consumed 360g of apples as part of an acute feeding study. Postprandial urine samples were collected at 2, 4 and 24 hours post-apple consumption for analysis. Subsequently a dose-response study was performed where volunteers consumed different portions of apples (50g, 100g or 300g) and fasting urine samples were collected for analysis. Xylose was quantified analysed on a 600-MHz Varian NMR spectrometer using the first increment of a NOESY pulse sequence. Dose-response data was used to develop calibration curves to determine apple intake in an independent free-living cohort (n=565) and used to classify individuals into categories of apple-intake. Multivariate analysis of NMR metabolomic data and time-series plots revealed that urinary xylose concentrations increased significantly at 4h post-apple consumption (2.19µM/osm), compared to the control food-broccoli (0.34µM/osm). In the dose-response study, urinary xylose concentrations demonstrated a linear increase as apple-intake increased (r=0.406; p<0.0001). Urinary xylose concentrations quantified in the free-living cohort (0.05 to 1.46mM) obtained strong agreement between biomarker-based intake classification and self-reported intake classification. Urinary xylose increased with increasing apple-intake. Xylose performed well as a ranking biomarker for grouping into apple-intake categories. Future work will combine xylose with other markers which may allow for determination of intake at an individual level.
## SESSION 18: FOOD APPLICATIONS 2

Wednesday, June 26

1:30 p.m. – 3:15 p.m.

18D 2:35 p.m. – 2:55 p.m.

Brainfood metabolomics study (Icebreaker, Brave sub-study)

**PRESENTING AUTHOR:** Kati Hanhineva, Afekta Technologies Ltd., Finland

**CO-AUTHORS:** Kati Hanhineva, Marika Laaksonen, Sanna-Maria Hongisto, Juhani Sibakov, Heli Diaz, Anton Mattsson, Ville Koistinen, Jussi Loponen

**Background:** Cognitive performance is related to glucose metabolism and metabolic activation that are regulated by dietary factors. We studied the effects of brain-friendly diet (Brainfood) on metabolic and physiological parameters and cognitive performance in office workers at assumed metabolic risk (Brave study). Materials and methods: We conducted a diet-switch, 4-week intervention study on 84 volunteers with elevated plasma LDL levels in pre-screening. The Brainfood diet focused on regular meal frequency and optimal intake of polyunsaturated fats, fibre and salt, whereas the control diet was a typical western diet. Plasma samples were collected at the end of the lead-in, control and intervention periods, and analysed using liquid chromatography mass spectrometry (UPLC-QTOF-MS). Intervention efficacy was determined with a linear mixed model, and the fold changes of the metabolite levels were tested with t-tests corrected with Benjamini-Hochberg false discovery rate (FDR). Results: In total, we identified 37 differential metabolites (FDR-corrected p < 0.05), including acylcarnitines, amino acids, choline, 3-carboxy-4-methyl-5-propyl-2-furanpropionic acid (CMPF), methylimidazoleacetic acid, monoacylglycerols, phospho-lipids, piperine, and retinol. Several phosphatidylcholines and plasmalogens containing polyunsaturated fatty acids increased after the Brainfood diet, whereas lipids containing saturated or monounsaturated fatty acids decreased. The individual variability in metabolites was larger compared to the intervention effect. Conclusions: The Brainfood diet increased levels of CMPF and polyunsaturated fatty acid-containing phospholipids, likely originating from the intake of fatty fish. The reduced consumption of animal fats decreased their corresponding fatty acids in the lipid profile. Increased 3-methylhistidine was observed as a potential marker of poultry and plant-based protein intake.

18E 2:55 p.m. – 3:10 p.m.

Mass spectrometry based non-targeted metabolomics enables the identification of Amadori products in feces of formula-fed infants

**PRESENTING AUTHOR:** Alesia Walker, Helmholtz Zentrum München, Research Unit Analytical BioGeochemistry, Germany

**CO-AUTHORS:** Nina Sillner, Daniel Hemmler, Monika Bazanella, Silke S. Heinzmann, Dirk Haller, Philippe Schmitt-Kopplin

Non-targeted metabolomics can be used to identify food markers, without prior focusing on a set of small molecule ingredients or known food metabolites. Our interest was to investigate fecal metabolite profiles of breast- and formula-fed infants during the first year of life by LC-MS/MS and a subset by FT-ICR-MS. We observed that fecal samples of one month old infants, fed with whey-based formula milk, were dominated by four m/z values assigned as nitrogen containing compounds (C18H34N2O8, C24H44N2O13, C12H24N2O7 and C18H34N2O12), analyzed by FT-ICR-MS. HMBD annotation using m/z values resulted in one putative matching of fructosyllysine (FruLys), which is one of the most abundant Amadori products derived from food. Identification of four putative Amadori products was done with HILIC LC-MS/MS. Fragmentation experiments showed loss of a dipeptide for two features and multiple loss of water for all features, which is typical for glucose/ lactose moieties. The dipeptide fragment was assigned to leucylisoleucine (Leulle), which is present at the N-terminal sequence of the major whey protein β-lactoglobulin. The other two fragmented features showed typical lysine fragments. Based on the fragmentation, we identified two Leulle and two Lys Amadori products (FruLeulle, LactulosylLeulle, FruLys and LactulosylLys). Three of them were synthesized, fractionated and characterized by NMR, while FruLys was available as authentic chemical standard. All compounds were not detected in breastfed children and fecal levels of Amadori products decreased over time in formula-fed children due to solid food introduction. Thus, Leulle Amadori compounds could serve as food markers for consumption of whey-based formula milk.
## SESSION 19: DATA INTEGRATION & DATA BASING 2

Wednesday, June 26

1:30 p.m. – 3:15 p.m.

**19A Session Keynote**
1:30 p.m. – 2:00 p.m.

The UniProt, Rhea, and SwissLipids knowledge resources for metabolomics and lipidomics

**PRESENTING AUTHOR:** Alan Bridge, Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Switzerland

**CO-AUTHORS:** Alan Bridge, Anne Morgat, Thierry Lombardot, Robin Liechti, Teresa Batista Neto, Sebastien Gehant, Parit Bansal, Jerven Bolleman, Kristian Axelsen, Lucila Aimo, Nevila Hyka-Nouspikel, Lou Götz, Dmitry Kuznetsov, Anne Gleizes, Anne Niknejad, Elisabeth Coudert, F Gisou van der Goot, Howard Riezman, Nicole Redaschi

Our group specializes in the development and maintenance of expert curated knowledge resources for the life sciences. Here we describe recent work designed to improve the utility of these knowledge resources for integrated computational and experimental analyses of metabolic systems. Our starting point for this work is Rhea (www.rhea-db.org), a comprehensive expert-curated knowledgebase of over 11,500 biochemical reactions that uses the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules to describe reaction participants, their chemical structures, and chemical transformations. We recently introduced Rhea as the standard for the annotation of enzymatic reactions in the UniProt Knowledgebase (UniProtKB, at www.uniprot.org). UniProtKB is a reference resource of protein sequences and functional annotation that currently includes over 150 million sequences and thousands of proteomes from all branches of the tree of life. The introduction of Rhea will significantly enhance the utility of UniProtKB as a basis to integrate and analyse metabolomic, proteomic and genomic data, to generate and annotate metabolic networks and models, to mine reaction data for pathway prediction and metabolic engineering, and to map metabolites to human diseases and associated genes and variants. We will describe selected tools and services that leverage Rhea and UniProt and practical examples of how to use them. We will conclude by describing how we use curated knowledge of lipid metabolic pathways in Rhea and cheminformatics approaches to build SwissLipids (www.swisslipids.org), a resource of over 500,000 known and theoretically possible lipid structures and biological knowledge that is fully mapped to ChEBI, Rhea and UniProt.

**19B 2:00 p.m. – 2:20 p.m.**

**RIKEN Plant Metabolome MetaDatabase: an integrated plant metabolome data repository based on the semantic web**

**PRESENTING AUTHOR:** Atsushi Fukushima, RIKEN Center for Sustainable Resource Science, Japan

**CO-AUTHORS:** Mikiko Takahashi, Nozomu Sakurai, Toshiaki Tokimatsu, Hideki Nagasaki, Hideki Hirakawa, Takeshi Ara, Makoto Kobayashi, Miyako Kusano, Kazuki Saito, Masanori Arita, Norio Kobayashi

Metabolome data provide new opportunities to gain a deeper understanding of plant metabolism relevant to both, plant and human health benefits. Major public repositories for general metabolome data have been launched over the past decade, but in terms of data sharing, many aspects remain unresolved especially for improving reanalysis, reusability and reproducibility. In this study, we developed the RIKEN Plant Metabolome MetaDatabase (RIKEN PMM, http://metabobank.riken.jp/), which stores gas chromatography-mass spectrometry-based (i.e. GC-MS-based) metabolite profiling data of plants together with their detailed experimental metadata, including sampling and experimental procedures. Our metadata are described using the Resource Description Framework (RDF) and standardised vocabularies, such as the Metabolomics Standardization Initiative Application Ontology (MSI-AO), to integrate with other life and biomedical science data on the World Wide Web. The RIKEN PMM implements intuitive and interactive operations for plant metabolome data, including raw data, mass spectra and metabolite annotations. The RIKEN PMM is suitable not only for scientists who are interested in metabolomic phenotypes but also for researchers who would like to investigate plant metabolomics approaches. Our framework can provide enough metadata required for reanalyzing and reusing the raw data, and will contribute to the development of yet another general-purpose metabolomics repository.

**19C 2:20 p.m. – 2:35 p.m.**

**Contextualizing Metabolomics Data by Integrating Text Mining and Machine Learning**

**PRESENTING AUTHOR:** Magnus Palmblad, Leiden University Medical Center, Netherlands

The scientific literature contains a wealth of information for text mining and machine learning in the public domain, including Europe PMC with 35 million titles and abstracts, and 2.3 million open access papers. Much work has been done on extracting functional protein interactions and linking genes to diseases. Here I will describe how text mining chemical entities, with emphasis on metabolites, can be combined with machine learning and large-scale prediction of physicochemical properties to guide the selection of analytical methods in metabolomics, assess bias in metabolomics datasets, and place metabolomics data in wider contexts. The method is automated in scientific workflows, greatly facilitating its reuse and adaptation. Particular emphasis is placed on how to visualize the results from millions of named-entity recognitions in tens of thousands of articles in a single, informative, figure. The visualization styles may be new in the text mining but should be intuitive to practitioners of mass spectrometry-based metabolomics. Applications include drug development, data integration and business intelligence.
<figure><img src="image_27.png" /></figure>

<figure><img src="image_28.png" /></figure>

## SESSION 19: DATA INTEGRATION & DATA BASING 2

Wednesday, June 26

1:30 p.m. – 3:15 p.m.

**19D 2:35 p.m. – 2:55 p.m.**

Metabolic Reaction Network-based Recursive Metabolite Annotation for Untargeted Metabolomics

**PRESENTING AUTHOR:** Zheng-Jiang Zhu, Chinese Academy of Sciences (CAS), China

Large-scale metabolite annotation is a challenge in liquid chromatogram-mass spectrometry (LC-MS)-based untargeted metabolomics. Here, we develop a metabolic reaction network (MRN)-based recursive algorithm (MetDNA) that substantially expands metabolite annotations without the need for a comprehensive standard spectral library. Metabolites and their reaction-paired neighbor metabolites tend to share similar MS2 spectra due to structural similarity. Based on this rationale, MetDNA characterizes initial seed metabolites using a small tandem spectral library, and utilize their experimental MS2 spectra as surrogate spectra to annotate their reaction-paired neighbor metabolites which are subsequently served as the basis for recursive analysis. We further showcase the utility and versatility of MetDNA using different LC-MS instrumentations, data acquisition methods, and biological sample types, and demonstrate that about 2,000 metabolites can cumulatively be annotated from one experiment. MetDNA largely expands the annotation of metabolites, thereby allowing quantitative assessment for not just metabolic pathways but also multi-omic studies, such as integrative analysis between metabolomics and transcriptomics.

**19E 2:55 p.m. – 3:10 p.m.**

Sparse Multi-block PLS for Selection of Related Signals in Multi-platform Metabolomics Data

**PRESENTING AUTHOR:** Timothy Ebbels, Imperial College London, United Kingdom

**CO-AUTHORS:** Kate Leary, Ibrahim Karaman, Goncalo Graca, David Herrington

Combining data from multiple assays is of great value when attempting to identify unknowns in metabolomics. A key problem is how to associate signals from the same unknown in different assays. Statistical correlation can be helpful in finding associated signals, but is susceptible to noise, outliers and artefacts. Multivariate models are robust to these interferences and have proven their worth in many areas of metabolomic data modelling. Here, we evaluate sparse Multiblock PLS (sMBPLS) regression as an approach to integrate multiplatform data, with the objective of linking signals from the same molecule, to aid the process of identifying unknowns. We use real human serum NMR and LCMS data from a large cohort study with multiple epidemiological outcome variables. To evaluate the approach, we electronically spike signals at realistic levels into the real data. We find that signals from the same metabolite can be associated by this approach with a high degree of accuracy (AUROC=0.86 at 0.25 effect size, 10 spikes per block). We develop a novel visualisation tool allowing users to discover associated signals based on the sMBPLS model. Application to real outcome data shows that the method is able to associate signals from the same metabolites across multiple assays, indicating that this is a promising approach to aid identification of unknowns and discovery of biomarkers in multiplatform metabolomic data.

## SESSION 20: REGULATORY SESSION

Translating metabolomics from academic science into regulatory practice: challenges and progress in pharmacology and toxicology

See Page 9
## SESSION 21: INFECTION AND IMMUNITY

Wednesday, June 26

3:45 p.m. – 5:30 p.m.

**21A Session Keynote**
**3:45 p.m. – 4:15 p.m.**

Understanding the metabolic perturbation in severe fever with thrombocytopenia syndrome

**PRESENTING AUTHOR:** Zeping Hu, Tsinghua University, China

Severe fever with thrombocytopenia syndrome (SFTS) caused by a recently identified bunyavirus, SFTSV, is an emerging infectious disease with extensive geographical distribution and high mortality. Progressive viral replication and severe thrombocytopenia are key features of SFTSV infection and fatal outcome, whereas the underlying mechanisms are unknown. We revealed arginine deficiency in SFTS cases by performing metabolomics analysis on two independent patient cohorts, suggesting that arginine metabolism by nitric oxide synthase and arginase is a key pathway in SFTSV infection and consequential death. Arginine deficiency was associated with decreased intraplatelet nitric oxide (Plt-NO) concentration, platelet activation, and thrombocytopenia. An expansion of arginase-expressing granulocytic myeloid-derived suppressor cells was observed, which was related to T cell CD3-ζ chain down-regulation and virus clearance disturbance, implicating a role of arginase activity and arginine depletion in the impaired anti-SFTSV T cell function. Moreover, a comprehensive measurement of arginine bioavailability, global arginine bioavailability ratio, was shown to be a good prognostic marker for fatal prediction in early infection. A randomized controlled trial demonstrated that arginine administration was correlated with enhanced Plt-NO concentration, suppressed platelet activation, and elevated CD3-ζ chain expression and eventually associated with an accelerated virus clearance and thrombocytopenia recovery. Together, our findings revealed the arginine catabolism pathway-associated regulation of platelet homeostasis and T cell dysregulation after SFTSV infection, which not only provided a functional mechanism underlying SFTS pathogenesis but also offered an alternative therapy choice for SFTS.

**21B 4:15 p.m. – 4:35 p.m.**

Hijacking of host cellular function by opportunistic pathogens during intracellular infections

**PRESENTING AUTHOR:** Volker Behrends, University of Roehampton, United Kingdom

**CO-AUTHORS:** Natalia Bravo-Santano, James K Ellis, Luis M Mateos, Yolanda Calle, Hector C Keun, Michal Letek

Staphylococcus aureus is one of the leading causes of hospital-acquired infections and a major human pathogen worldwide. As a facultative intracellular pathogen, S. aureus is able to invade both phagocytic and non-phagocytic cells. The emergence of multidrug-resistant strains, such as methicillin-resistant S. aureus (MRSA) has made treating S. aureus infections significantly more complicated. Therefore, there is an urgent need to find novel therapies. This study aims to identify and target host molecular pathways exploited by MRSA during intracellular infection with a view of identifying possible host-directed therapies. We employed stable-isotope labelling coupled to GC/MS and NMR-based metabolic profiling to investigate the impact of bacterial infection on host carbon metabolism. We found extensive metabolic re-routing (a block of mitochondrial uptake of pyruvate resulting in a decreased flux through the TCA cycle from glucose) and detected several distinct metabolic changes that suggested starvation-induced autophagy in infected cells. These changes included increased uptake but lower intracellular levels of glucose, low abundance of several essential amino acids as well as markedly upregulated glutaminolysis. We identified the molecular cascade activated in our infection model and showed that most of the autophagosomes detected in infected cells did not contain bacteria, suggesting that S. aureus induces the autophagic flux during cell invasion for energy generation and nutrient scavenging. Accordingly, drug-induced inhibition of AMPK, the responsible host kinase, hampered S. aureus intracellular proliferation. Our findings show that targeting host pathways essential for MRSA survival is a viable therapeutic strategy against this versatile pathogen.

**21C 4:35 p.m. – 4:50 p.m.**

Diagnosis of Aspergillosis based on metabolomics data – application of relative expression analysis-RXA to minimize interindividual metabolic differences

**PRESENTING AUTHOR:** Joanna Godzien, Medical University of Bialystok, Clinical Research Centre, Poland

**CO-AUTHORS:** Joanna Godzien, Marcin Czajkowski, David Rojo-Blanco, Cristina Cunha, Katrien Lagrou, Johan A. Maertens, Coral Barbas, Agostinho Carvalho

Invasive aspergillosis (IA) is an infection that affects immunocompromised hosts. Due to the increasing occurrence and despite available antifungal therapy, IA is a leading cause of mortality in the ICU. To assess this complex problem a multiplatform metabolomics approach was implemented. Serum and bronchoalveolar lavage fluid samples from immunosuppressed patients, with and without IA, were profiled across three analytical platforms including LC/MS, GC/MS, and CE/MS. Due to the large intra-group variation caused by the variety of medical complications, apart from canonical chemometrics, a novel approach was applied. Exploitation of the data was performed using the Top Inter-GEne Relation-(TIGER) machine learning classifier, which focuses on the relative order of features rather than their raw values. The specialized evolutionary algorithm extends the concept of Relative Expression Analysis-(RXA) and enables the search for complex interactions and patterns in the metabolomics data. In this way, we found several interesting metabolic classifiers. As an example: if the concentration of glutamine is higher than the concentration of amino-caprylic, then with 80% probability such sample can be classified as a case. Moreover, changes between native forms of metabolites and their epi-forms were evaluated, revealing for example significance of methylation processes over acetylation. Extensive data analysis of two types of biological samples and multiplatform data integration allowed to determine metabolic differences between infected and uninfected patients. This leads us to define the metabolic signature of the predisposition to the IA. This metabolic signature was supported by clinical parameters to characterize the profile of such patients better.
## SESSION 21: INFECTION AND IMMUNITY

Wednesday, June 26

3:45 p.m. – 5:30 p.m.

**21D 4:50 p.m. – 5:10 p.m.**

Alterations of systematic metabolism upon viral infection: from metabolite profiling to isotope tracing

**PRESENTING AUTHOR:** Kristaps Klavins, CeMM - Research Center for Molecular Medicine, Austria

**CO-AUTHORS:** Alexander Lercher, Bettina Gürtl, Andreas Bergthaler

Viral infections cause severe perturbations of a host metabolome that goes along with inflammation, tissue damage, and metabolic reprogramming. In this study, we investigated changes in systematic metabolism caused by chronic viral infection. We infected mice with lymphocytic choriomeningitis virus which is a well-established and pathophysiological relevant model for chronic viral infection. We performed targeted quantitative profiling of more than 180 serum metabolites, including amino acids, biogenic amines, acylcarnitines, sphingolipids and glycerophospholipids from infected C57BL/6J wildtype (WT) mice, by LC-MS/MS. We observed wide-spread metabolic alterations and, most notably, metabolites of the urea cycle were significantly changed. The urea cycle is a central metabolic pathway expressed in the liver. To fully characterize infection-induced changes of this pathway, we established a LC-MS based method for quantification of all urea cycle metabolites and the closely connected tricarboxylic acid cycle. This method allowed us to confirm previous results as well as provided evidence of infection-induced reprogramming of the urea cycle. To validate these findings we performed an in vivo tracing experiment using 13C labeled metabolites. For reliable isotopologue detection, we employed high-resolution mass spectrometry and identified significant changes in degradation and synthesis rates of metabolites. Employing and integrating complementary metabolomics approaches led to the identification of virus-induced reprogramming of the urea cycle and altered systemic metabolite levels during chronic viral infection.

**21E 5:10 p.m. – 5:25 p.m.**

Characterisation of the human milk lipidome using liquid chromatography-ion mobility spectroscopy-mass spectrometry reveals novel lipids

**PRESENTING AUTHOR:** Alexandra George, The University of Western Australia, School of Molecular Sciences, Australia

**CO-AUTHORS:** Melvin Gay, Donna Geddes, Kevin Murray, Robert Trengove

The human milk (HM) lipidome is complex, with inter- and intra-individual variation present during the day, throughout a feed, and throughout lactation. These lipids provide over 50% of the daily infant energy requirements, and are known to contribute to immune cell metabolism and activation, and neural and retinal development. Although years of HM research have investigated the total fatty acid composition, these fatty acids are predominantly packaged as triacylglycerides in fat globules. The positioning of the fatty acids on the triacylglyceride is critical for infant absorption, therefore analysis of individual fatty acids does not accurately represent the HM lipidome and its physiological relevance to the infant. Liquid chromatography-ion mobility spectroscopy-mass spectrometry (LC-IMS-MS) methodology has demonstrated its ability to more comprehensively characterize triacylglycerides in bovine milk, but has not been applied to HM. To characterise the HM lipid profile, untargeted LC-IMS-MS was carried out on HM samples from a longitudinal cohort. Over 200 triacylglycerides and their fatty acid arrangements were identified, many of which have not previously been identified in HM. The abundance of each triacylglyceride, such as C61H106O6 (22:0/16:0/20:4), was lower in pre-feed samples and higher in post-feed samples, and typically increased throughout the day. C61H106O6 has potent antimicrobial properties and was measured in significantly lower concentrations in the milk of mothers with infants who more frequently suffered infections. The additional orthogonal separation offered by ion mobility can more accurately profile HM lipids and provides an opportunity to fully characterise the HM lipidome and its impact on infant outcomes.
## SESSION 22: ENVIRONMENT & TOXICOLOGY

Wednesday, June 26

3:45 p.m. – 5:30 p.m.

**22A Session Keynote**
3:45 p.m. – 4:15 p.m.

Metabolomics and toxicity studies of zebrafish embryos exposed to environmental contaminants

**PRESENTING AUTHOR:** Pim Leonards, Vrije Universiteit, Netherlands

**CO-AUTHORS:** Jessica Legradi

Per- and polyfluorinated alkylated substances (PFASs) have been widely used as organic surfactants in industrial and consumer products. While these applications made PFASs very appealing their properties make PFAS very persistent in the environment. In this study we performed a chemical alternatives assessment using metabolomics between PFOA and PFOS and alternative chemicals to be able to select environmentally friendly compounds. Zebrafish embryos (Danio rerio) were chronically and acutely exposed (0.1 µM, 1 µM, 10 µM) to PFOA and PFOS and its alternatives PFHxS, PFBS, siloxanes (D4, D5 and TMS), and GenX to study the mechanism of toxicity. No significant effects on mortality, visual developmental abnormalities, and swimming activity were observed for all compounds. Embryos were subjected to further investigation in an attempt to address potential genetic and metabolomic effects. Transcription of the DNA damage gene was significantly up-regulated by over 2-fold relative to the control vs. PFOA, PFHxS, PFOS and GenX. Interestingly, the lipid metabolism gene was up-regulated by over 2-fold in the embryos exposed to PFOS and GenX. These observations correspond well with the metabolomics data that showed the regulation of many lipids (PC, PE, TAG, SM). Based on the results of this study, alterations in lipid metabolism (glycerophospholipids) may be a metabolic pathway affected by both PFASs and their alternatives. GENX, as alternative to PFOA, displayed a pattern of similar activity as the PFASs. The alternatives D4, D5 and TMS appears to have a lower impact on metabolic pathways (e.g. lipids) than PFOA.

**22B 4:15 p.m. – 4:35 p.m.**

Gestational and post-natal exposure to ambient air pollution: a metabolomics approach

**PRESENTING AUTHOR:** Marina Tavares, University of Sao Paulo, Brazil

**CO-AUTHORS:** Andréa T. Faccio, Aline Klassen, Amanda V.B. das Dores, Daniel R. Oliveira, Lucas H.F. da Silva, Mariana M. Veras, Paulo Saldiva, Massuo J. Kato, Ernani Pinto Jr., Joao P.S. Farah

According to WHO (2016), 91% of people living in cities are exposed to air pollution in levels above the recommended limits for air quality. Ambient air pollution has been associated with a number of acute and chronic conditions, including obstructive pulmonary disease, ischaemic heart disease, and lung cancer. Therefore, there is a pressing interest in understanding the underlying metabolic mechanisms by which atmospheric air pollution affects human health. An untargeted metabolomics approach was envisioned here to evaluate the effects of pre- and post-natal exposure to air pollution. A cohort of 24 pregnant mice was exposed during pregnancy to either filtered air or PM2.5 enriched polluted air. Offspring were further exposed: filtered air (n=35), and polluted air (n=39). Urine samples were collected and analyzed by HILIC-MS (zwitterionic-sulfobetaine column). Raw data were preprocessed (XCMS) and statistically evaluated using uni- and multi-variate approaches (SIMCA-P). Group classification clearly indicated the occurrence of metabolic alterations in mice as a result of both maternal and offspring exposure. For the mothers, 108 metabolites were putatively identified out of 137 discriminant metabolites and many chemical classes were impacted such as peptides, fatty acids, amines, and ketones. For the offspring, several group comparisons were possible, resulting in alterations of metabolic pathways associated to histamine and tryptophan biochemistry. A deeper evaluation of the metabolic pathways revealed by this work can greatly contribute to understand the link between air pollution and disease development, and perhaps, lead to the setting of new regulations and public health initiatives.

**22C 4:35 p.m. – 4:50 p.m.**

Association between coffee consumption, plasma metabolites and hypertension risk

**PRESENTING AUTHOR:** Wei Jie Seow, National University of Singapore, Singapore

**CO-AUTHORS:** Wei Jie Seow, Wenchi Pan, Deron R. Herr, Federico Torta, Chin Meng Khoo, Markus R Wenk, Tai E Shyong, Rob M. van Dam

**Background:** Coffee is one of the most popular beverages in the world. It is known that coffee drinking is associated with short-term spikes in blood pressure. However, the associations between coffee consumption, blood metabolites and hypertension risk in Asian populations are still largely unknown. **Objectives:** To assess the associations between dietary coffee consumption and hypertension risk, with potential mediation via blood metabolites. **Methods:** We used data from 3,020 participants of the population-based Singapore Prospective Study Programme (SP2) cohort. Amino acids, acylcarnitines and lipids in pre-diagnostic blood were measured using mass spectrometry. Logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for the association between coffee, metabolites and hypertension risk, adjusting for potential confounders. **Mediation analysis** was used to estimate the proportion of mediated effect via the metabolites on the association between coffee consumption and hypertension risk. False discovery rate (FDR) was evaluated using the Benjamini-Hochberg method. **Results:** Coffee consumption was associated with a 13% higher risk of incident hypertension for each cup of coffee consumed per day (OR=1.13,95%CI=1.02-1.26,P-value=0.024). Coffee was also associated with significant changes in the levels of 59 metabolites (FDR<10%), including sphingolipids and acylcarnitines. Levels of three metabolites (Cer d18:1/22:0,SM d16:1/24:0,HexCer d16:1/22:0) were directly associated with hypertension risk. Part of the putative effect of coffee intake on increasing hypertension risk was estimated to be mediated via these metabolites. **Conclusions:** Higher coffee consumption was found to be associated with higher hypertension risk, with possible partial mediation through blood ceramides and sphingomyelin concentration.
SESSION 22: ENVIRONMENT & TOXICOLOGY

Wednesday, June 26

3:45 p.m. – 5:30 p.m.

22D 4:50 p.m. – 5:10 p.m.

Small molecules and lipids preserved over thousands of years in mummified humans

PRESENTING AUTHOR: Kevin Quinn, University of Colorado Anschutz, United States

CO-AUTHORS: Charmion Cruickshank-Quinn, Spencer Mahaffey, Roger Powell, Richard Reisdorph, Nichole Reisdorph

Background: The mummified remains of ancient persons can provide clues about their environment, health, and death. While previous studies have focused on genetic and proteomic analyses, few studies have utilized untargeted metabolomics for either exploratory purposes or to gain insight into the mummification process. The goal was to determine differences associated with age and mummification process. Methods: The tissues from four, naturally preserved mummies were examined: Oetzi the Iceman (5,300 years old), Scythian Warrior (2,400 years old), Scythian Princess (2,400 years old), and a mummy found in an apartment in Vienna, Austria (4 years old). Samples were prepared using solid phase extraction to obtain the following four fractions: aqueous small molecules, fatty acids, neutral lipids, and phospholipids. Fractions were analyzed using liquid chromatography mass spectrometry (LC-MS) in positive and negative ionization mode with electrospray time-of-flight MS. Results: There were between 2,400 and 3,070 compounds detected in the mummified tissue samples. These compounds included oxidative stress-related compounds and bacterial/microbiome-associated metabolites. The lipid peroxidation product, 4-oxo-nonenal was detected in all the mummified samples, while urobilin (a degradation product of heme), and the antioxidant uric acid were only detected in the apartment mummy. The lipid PI(40:3) showed a pronounced decrease with time based on the age of the mummy that became undetectable at 5,300 years. The top enriched pathways (FDR < 0.0001) were sphingolipid metabolism and glycerophospholipid metabolism. Conclusion: Results suggest that certain small molecules and lipids can survive for millennia following the mummification process and that oxidation could indicate length of mummification.

22E 5:10 p.m. – 5:25 p.m.

Food preservative zinc oxide nanoparticles (ZnONPs) induces neurobehavioral deficits in mice with altered gut microbiome and dysregulated serum and hippocampus metabolome

PRESENTING AUTHOR: Chang Chen, Chongqing Medical University, China

CO-AUTHORS: Xuejun Jiang, Xia Qin, Shanshan Zhang, Yujia Zhang, Lulu Bai, Tianxiong Wang, Zhen Zou, Chengzhi Chen

Zinc oxide nanoparticles (ZnONPs) is widely used as food preservative, but its impact on health has not been fully elucidated. We studied the effect of orally administrated ZnONPs on the neurobehavior of mice, as well as the possible mechanism from the perspective of gut microbiome and serum and hippocampus metabolome. Results show that mice administrated with ZnONPs (n = 8) at equivalent dose to human food exhibited lower numbers of cross platform, longer escape latency in Morris water maze, and shorter total distance in open field test than their counterparts (n = 8). Eight bacterial clades were downregulated, while seven upregulated in the gut of mice in ZnONPs group. Twenty-six differential metabolites were found from serum and four from hippocampus. Correlation analysis found that the differential bacterial clades had a close relationship with the differential metabolites. We conclude that oral administration of ZnONPs may cause neurobehavioral deficits in mice, which is associated with a crosstalk between altered gut microbiome and serum/hippocampus metabolome.
## SESSION 23: NEW INSTRUMENTATION

Wednesday, June 26

3:45 p.m. – 5:30 p.m.

**23A Session Keynote**
3:45 p.m. – 4:15 p.m.

Integration of MS imaging and LC-MS techniques – discovering tissue heterogeneity with the accuracy and depth of traditional profiling tools

**PRESENTING AUTHOR:** Matthew Lewis, Imperial College London, United Kingdom

LC-MS, GC-MS and NMR spectroscopy are generally considered to be the core analytical approaches for metabolic profiling, however they are far from optimally applied in a number of cases including the analysis of biological tissues and high throughput analysis. At Imperial College London, capitalizing on the depth of experience within our National Phenome Centre and mass spectrometry imaging (MSI) facilities, we are advancing the integration of metabolic profiling approaches in an effort to realise the broader potential of technology-driven translational medicine. Although metabolic imaging by mass spectrometry is a sensible approach for the analysis of highly heterogeneous tissues, the approach suffers from poor sensitivity and the lack of ion structure information such as MS/MS or collisional cross section. Combining MSI with LC-MS can potentially solve these problems and also serve as a core for the integration of clinical chemistry and histopathology. Our approach utilizes serial sections, where one section is subjected to metabolic imaging by desorption electrospray ionization (DESI). The MSI data is analysed by supervised multivariate methods to identify histologically homogeneous segments and then the tumour part is segmented further using an unsupervised approach. The positions of discrete sub-histological phenotypic segments are registered on the following sections and dissected using laser capture microdissection. The resulting samples are extracted and subjected to LC-MS-based metabolic profiling. This approach allows us to perform traditional metabolite identification, spatially resolved quantification and detection of low-abundance species in tissues. Furthermore, the approach also allows the broader integration of other systems biology tools (genomics, transcriptomics, proteomics) with histology.

**23B 4:15 p.m. – 4:35 p.m.**

Mapping Hydrophilic Intermediates of the Central Carbon and Energy Metabolism (CCEM) by Ion Pairing and Ion Exchange Chromatography – Tandem MS

**PRESENTING AUTHOR:** Gerd Balcke, Leibniz-Institute of Plant Biochemistry, Germany

**CO-AUTHORS:** Mohamad Saoud, Ludger Wessjohann, Alain Tissier

Metabolomic analysis of hydrophilic metabolites is required in many research areas such as cancer biology, infection studies, diabetes, plant biology and in the attempt to understand basic principles of cellular regulation. However, quantitative and reproducible analysis of charged and hydrophilic CCEM intermediates is a challenging task which requires specific quenching/ extraction methods along with protection against degradation and inter-metabolite conversion. Using a combinatorial approach of ion pairing and ion exchange LC-MS/MS we separated and detected 152 phosphorylated, zwitterionic and carboxylated hydrophilic metabolites. We assessed cold quenching and cryo-extractions under various pH conditions and categorized stability conditions for metabolite classes such as nucleotides, nucleosides, CoA esters, TCA acids, sugar bisphosphates, etc., in different cell extracts. We demonstrate that under specific pH conditions even very labile metabolites such as CoA esters, nucleotides, sugar bisphosphates, GSH or NAD(P)(H) cofactors can be stabilized over 24 h at 4 °C. By spiking various non-labeled metabolites to U13C-labelled E.coli cells immediately before cold quenching/extraction we quantified the turnover and interconversion rates of various metabolites and pinpoint minimum bias conditions for the analysis of small molecule intermediates of the CCEM. We provide full solutions to assess CCEM intermediates of prokaryotes (in suspension), cancer cells (adherent) and snap-frozen plant tissue.

**23C 4:35 p.m. – 4:50 p.m.**

High-Resolution µ-scaled Magic-Angle Spinning NMR Mapping of diseased rat brains

**PRESENTING AUTHOR:** Covadonga Lucas-Torres, CEA Saclay, France

**CO-AUTHORS:** Yusuke Nishiyama, Alan Wong

In vivo MRS is a powerful spectroscopic technique for unveiling the metabolic distribution in tissue lesions. However, it can be limited by the spectral and spatial resolution for a comprehensive and unbiased metabolomic investigation. Localized NMR-based metabolic profiling on excised tumorous rat brain has been accomplished herein for the first-time under the recently introduced HR-µMAS technology (1). A total of 108 biopsies have been systematically sampled from 4 specific brain slices (2 control and 2 tumor) with an excellent spectral resolution (6 ppb at 11.7 T) and spatial sampling resolution (a voxel of 0.6 mm3). These resolutions are superior to those acquired from today's advanced localized in vivo MRS (with MRI). The excellent spectral data quality has allowed 95% of the acquired data for generating reliable statistical models. The initial multivariate data analysis discriminates between control and tumor, allowing for a preliminary inspection of the data and identification of the principal metabolic profile of the tumor (i.e. increase in cholines, taurine and glucose; decrease in NAA). The superb resolution has also unbiasedly unfolded the increased level of glycine content, in which the signal in in vivo MRS is often overlapped with that of myo-inositol. Moreover, the study has also capitalized the good spatial sampling resolution and revealed the different metabolic distributions across the brain slice. This study with HR-µMAS NMR offers a glimpse of its potential for investigating µg-scaled tissue biopsy.
## SESSION 23: NEW INSTRUMENTATION

Wednesday, June 26

3:45 p.m. – 5:30 p.m.

23D 4:50 p.m. – 5:10 p.m.

Electroextraction-based sample preparation strategies for enrichment of low-abundant metabolites

**PRESENTING AUTHOR:** Peter Lindenburg, Analytical Biosciences & Metabolomics, Leiden Centre for Applied Bioscience, Leiden University, Netherlands

**CO-AUTHORS:** Amar Oedit, Yupeng He, Thomas Hankemeier

In biomass-limited samples, such as for example mouse brain tissue samples, the analysis of low-abundant metabolites remains a challenge as these metabolites fall below the limit of detection of these techniques. SPE- and LLE-based sample pretreatment procedures suffer from practical limitations (i.e. sample handling) when analyzing biomass-limited samples. Electroextraction (EE) is an electromigration-based sample pretreatment technique which depends on the application of an electric field over a liquid-liquid system that consists of immiscible organic donor and aqueous acceptor phases. The discontinuous electric field that is present in such liquid-liquid systems is the driving force behind the analyte enrichment capacity of EE. As a consequence, EE-based sample pretreatment improves the detection limits and enables analysis of low-abundant metabolites and is therefore highly suited for miniaturized, high-throughput metabolite analysis. Furthermore, it allows for efficient sample handling as well as pretreatment. EE specifically targets ionic analytes and is therefore very suited for analysis of the metabolome, which comprises ±80% of charged/chargeable metabolite species. Moreover, EE offers excellent possibilities for online integration in analytical platforms. This lecture presents analysis of low-abundant metabolites with several analytical platforms in which EE is incorporated, i.e. continuous-flow micro-EE, three-phase EE and hyphenated EE techniques (EE-DI-MS, EE-LC-MS and EE-CE-MS). A comparison between these platforms will be made and the great potential of EE-based strategies for enrichment of low-abundant metabolites and biomass-limited samples will be demonstrated.

23E 5:10 p.m. – 5:25 p.m.

How to automate boring lipidomic extraction?

**PRESENTING AUTHOR:** Justine Bertrand-Michel, MetaToul-Lipidomic, France

**CO-AUTHORS:** Julia Soullier, Aurélie Batut, Jessica Dalloux-Chioccioli, Anthony Tournadre, Pauline Le Faouder

Lipids are ubiquitous biomolecules essential to all life, found in every cellular type, ranging from the human body and vegetal organisms, down to bacteria. They have many different functions in cell structuration, energy storage and signalling so they are natural biomarkers for different diseases like cancer, cardiovascular disease, neurodegenerative disease, lung disease, their study and quantification are then crucial. Mass spectrometry (MS) coupled with liquid chromatography or gas chromatography is mainly used for global and specific analysis of lipids. But before their analysis, there is an important and time consuming step of sample preparation. Due to their amphiphilic properties, there are usually two types of extractions: liquid-liquid extraction (LLE) and solid phase extraction (SPE). LLE and SPE are two very long protocols which are tedious when there are massive numbers of samples. They can also be the source of many errors, considering the experimenter-dependant possible repeated artefacts. To circumvent this point and increase the analytical service delivery, a TECAN robot has been acquired by MetaToul-Lipidomic facility to automate the sample preparation. Due to the specificity of lipid extraction, the robot needs a lot of optimization. This presentation will show part of adaptation we had to perform to validate fatty acid, neutral lipid and phospholipid profiling. That was related to the precision of solvent sampling which implies new adjustment accuracy for each of them, adding air gap, but also to modify the speed... First lipidomic's results obtained with a complete automated sample preparation will be presented for liver and plasma sample.
## SESSION 24: NOVEL APPLICATIONS

Wednesday, June 26

3:45 p.m. – 5:30 p.m.

**24A Session Keynote**
3:45 p.m. – 4:15 p.m.

Metabolomics: Central Approach for Study of the Exposome

**PRESENTING AUTHOR:** Dean Jones, Emory University, United States

**CO-AUTHORS:** Edward T. Morgan, Choon-Myung Lee, Grant Singer, Ken Liu, Shuzhao Li, Young-Mi Go, Gary W. Miller

Most human disease occurs through interactions of environmental exposures with an individual's genome. The exposome is defined globally to include dietary, pharmacologic, industrial and personal use products to which an individual is exposed. Metabolomics methods are very powerful because they provide means to capture biologic responses to exposures. In many cases, metabolomics also supports detection and quantification of xenobiotic chemicals and their metabolites. This latter finding has allowed development of an analytical framework in which metabolomics connects external exposures, internal body burden of chemicals and their metabolites, biologic responses to exposure, and health and disease outcomes. Examples of this central role of metabolomics in environmental health research will be provided in the presentation. The talk will also summarize new efforts, as part of the Chemical Identification Discovery Cores of the US National Institutes of Health Common Fund Metabolomics Consortium, to identify large numbers of un-identified low abundance mass spectral signals found in biospecimens. In this research, we are using xenobiotic detoxification enzymes to develop tools to rapidly generate and confirm identities of such xenobiotic metabolites. We start with knowledge that about 80 xenobiotic transformation systems occur in mammals. Prior knowledge of these systems allows creation of reconstituted cell-free systems for selective biotransformation reactions and also creation of stably transfected cell lines with over-expression of specific biotransformation systems. By creating arrays of these biotransformation systems in a 96-well format, we have found that we can simultaneously generate a series of xenobiotic metabolites. Because xenobiotic metabolites of each biotransformation reaction can be predicted, analysis of reaction products using liquid chromatography with high-resolution mass spectrometry and targeted MSn supports high-throughput xenobiotic metabolite identification. Studies with well characterized xenobiotics with known metabolites establish the utility of the approach and also demonstrate generation of previously uncharacterized xenobiotic metabolites. With creation of 384-well and 1536-well formats, we anticipate that the method can support mega-scale metabolite identification for large (>10,000) chemical libraries.

**24B 4:15 p.m. – 4:35 p.m.**

Metabolomes of mitochondrial diseases and inclusion body myositis patients: treatment targets and biomarkers

**PRESENTING AUTHOR:** Vidya Velagapudi, FIMM, University of Helsinki, Finland

**CO-AUTHORS:** Buzkova Jana, Nikkanen Joni, Ahola Sofia, Hakonen Anna H, Sevastianova Ksenia, Hovinen Topi, Yki-Järvinen Hannele, Pietiläinen Kirsi H, Lönnqvist Tuula, Velagapudi Vidya, Carroll Christopher J, Suomalainen Anu

Mitochondrial disorders (MDs) are inherited multi-organ diseases with variable phenotypes. Inclusion body myositis (IBM), a sporadic inflammatory muscle disease, also shows mitochondrial dysfunction. We investigated whether primary and secondary MDs modify metabolism to reveal pathogenic pathways and biomarkers. We investigated metabolomes of 25 mitochondrial myopathy or ataxias patients, 16 unaffected carriers, six IBM and 15 non-mitochondrial neuromuscular disease (NMD) patients and 30 matched controls. MD and IBM metabolomes clustered separately from controls and NMDs. MDs and IBM showed transsulfuration pathway changes; creatine and niacinamide depletion marked NMDs, IBM and infantile-onset spinocerebellar ataxia (IOSCA). Low blood and muscle arginine was specific for patients with m.3243A>G mutation. A four-metabolite blood multi-biomarker (sorbitol, alanine, myoinositol, cystathionine) distinguished primary MDs from others (76% sensitivity, 95% specificity). Our omics approach identified pathways currently used to treat NMDs and mitochondrial stroke-like episodes and proposes nicotinamide riboside in MDs and IBM, and creatine in IOSCA and IBM as novel treatment targets. The disease-specific metabolic fingerprints are valuable "multi-biomarkers" for diagnosis and promising tools for follow-up of disease progression and treatment effect.

**24C 4:35 p.m. – 4:50 p.m.**

Boosting anti-doping screening through metabolomics

**PRESENTING AUTHOR:** Luca Narduzzi, Oniris – Laberca, France

**CO-AUTHORS:** Gaud Dervilly, Alexandre Marchand, Michel Audran, Bruno Le Bizec, Corinne Buisson

The World Anti-Doping Agency (WADA) prohibits the use of recombinant analogs of human hormones in any sport competition. Nonetheless, their use is suspected to be widespread among professional athletes who intake hormones in micro-doses, to obtain mild but continuous anabolic effects while reducing the detectability window. In particular, recombinant Growth Hormone (recGH) detection is very challenging: its turnover is within 24 hours after injection, with athletes' age and hormonal profile as strong confounding factors. Any hormonal treatment on humans has, by principle, an impact on metabolism. In this proof-of-principle study, applying LC-HRMS based metabolomics and lipidomics workflows on human bio-fluids (urine/plasma) we intended to trace indirectly recGH administration to (i) highlight specific patterns associated to treatment and (ii) investigate potential biomarkers. The study included a cohort of 16 well-trained volunteers split in two equal groups administered with 1) micro-doses of erythropoietin (EPO) or 2) micro-doses of EPO + recGH. The two groups showed different metabolic profiles, especially in their plasma lipids. The analysis also evidenced high intra-group variability, indicating a putative subject-specific effect of the hormones. To solve this issue, we normalized the data versus the time 0, therefore we could evidence the subject-specific profile associated to the treatment while tracking longitudinally "what" and "when" has been taken. Biomarkers identification highlighted several metabolic pathways affected by hormones intake, including triglycerides catabolism and amino-acids turnover. On the contrary, WADA-approved recGH tests were not able to individuate recGH intake. Metabolomics seems to be a promising tool to screen for illicit recGH administration.
SESSION 24: NOVEL APPLICATIONS

Wednesday, June 26

3:45 p.m. – 5:30 p.m.

24D 4:50 p.m. – 5:10 p.m.

A Novel Metabolomics Method for Quantitative Analysis of over 1,000 Metabolites

PRESENTING AUTHOR: Guowang Xu, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, China

CO-AUTHORS: Wangjie Lv, Lichao Wang, Qiuhui Xuan, Qingqing Wang, Xinjie Zhao, Chunxiu Hu, Xianzhe Shi, Xinyu Liu

Metabolomics is the science of studying endogenous small molecular metabolites. It has been developed since the end of last century and has made great progress in the fields of diseases, pharmaceuticals, agriculture, environment, etc. The most typical method is non-target method, it is hoped that "all" metabolites can be panoramically analyzed without bias. At this moment, thousands to tens of thousands of features can be obtained by ultra high-performance liquid chromatography (UHPLC)-mass spectrometry (MS), and hundreds of metabolites can be identified. Because of the complexity of metabolome, it is far from meeting the needs of systems biology research. It would be much better if we could increase the number of metabolites detected quantitatively to nearly 2,000. From an economic point of view, of course, the fewer methods the better. In view of this, this study focuses on how to develop novel LC-MS-based analytical methods for the quantitative detection of more than 1,000 metabolites. Following three scientific problems are covered, 1. Analytical peak capacity extending by using two-dimensional LC; 2. Quantitative ion-pair selection by using the computational metabolomics algorithm and SWAT method; 3. Metabolic profiling annotation and peak identification by studying structure-retention and structure-fragment relationships under the assistance of standard samples and Internet databases. Through the above measures, we have established a novel metabolomics method to quantitatively analyze more than 1,000 metabolites in biological samples (body fluid, tissue and cells). This report will show the latest results of this study.

24E 5:10 p.m. – 5:25 p.m.

Post-mortem changes in the metabolomic profiles of animal and human tissues

PRESENTING AUTHOR: Ekaterina Zelentsova, International Tomography Center SB RAS, Novosibirsk, Russia; Novosibirsk State University, Russian Federation

CO-AUTHORS: Lyudmila Yanshole, Vadim Yanshole, Olga Snytnikova, Yuri Tsentalovich

The analysis of post-mortem metabolomic changes in biological fluids opens the way to develop new methods for the estimation of post-mortem interval (PMI) which appears to be an actual problem in forensic medicine. Also, for humans, autopsy materials are often used as control tissues due to the inaccessibility of the tissues of a healthy patient (brain, eye tissues and others). For the correct use, a detailed description of the changes in the metabolomic content of autopsy tissues should be investigated. The combination of modern research methods - high frequency 1H NMR and high-resolution LC-MS - was used in this work. The quantitative levels of 61 metabolites in the rabbit and human serum, aqueous and vitreous humors (AH, VH) at different PMIs have been measured. The obtained results indicate the advantage of ocular fluids, AH and VH, over blood serum for the search of biochemical markers for the PMI estimation: the post-mortem metabolomic changes in the ocular fluids proceed slower than in blood, and the data scattering is lower. These changes are governed by two major factors: the degradation of the ocular tissues and the diffusion of metabolites from the body vascular systems into ocular fluids. Among the metabolites whose concentrations increase with time, the most significant and linear growth is found for glycerol (rabbit), betaine (human), and hypoxanthine, choline (both). The high potential of choline, glycerol and betaine as biomarkers for the PMI estimation is revealed in the present work for the first time. Supported by RFBR (Projects N°18-34-00137, 19-34-80008)
## SESSION 25: RESPIRATORY DISEASES

Thursday, June 27

8:45 a.m. – 10:00 a.m.

**25A Session Keynote**
8:45 a.m. – 9:15 a.m.

Omega-6 polyunsaturated fatty acid metabolites are associated with vitamin D levels in early life

**PRESENTING AUTHOR:** Jessica Lasky-Su, Brigham and Women's Hospital, United States

**CO-AUTHORS:** Mengna Huang, Rachel S. Kelly, Su H. Chu, Priyadarshini Kachroo, Kathleen Lee-Sarwar, Augusto A. Litonjua, Scott T. Weiss

Vitamin D is an important regulator of the immune system and low vitamin D levels are associated with a multitude of immunological disorders encompassing a broad range of diseases. The agnostic approach of untargeted metabolomics offers the opportunity to comprehensively examine changes in the metabolic profile associated with variations in vitamin D levels. The current study included the children who participated in Vitamin D Antenatal Asthma Reduction Trial, for whom plasma 25-hydroxyvitamin D [25(OH)D] and plasma metabolomics profiles were available at age 1 (n=451) and age 3 (n=407) years. Metabolomic profiling was conducted using ultrahigh-performance liquid chromatography and tandem mass spectrometry. After quality control, 624 known metabolites remained. We assessed the associations between individual metabolites and 25(OH)D level using linear regression adjusting for potential confounders. After correction for multiple comparisons, seven metabolites were significantly associated with 25(OH) D levels at both age 1 and age 3, including decreased concentrations of three members of the n-6 polyunsaturated fatty acid (n-6PUFA) metabolism pathway [linoleate(18:2), arachidonate(20:4), and docosapentaenoate(22:5)]. These n-6PUFA-metabolite-25(OH)D associations were replicated in older children from the Childhood Asthma Management Program (p<0.05). This analysis is the first to characterize the metabolic profile associated with 25(OH) D levels at two time points in early life, with replication in an independent population. The association between increased 25(OH)D levels and decreased concentrations of multiple n-6PUFA metabolites is important as both are involved in inflammatory processes, and evidence from cell and animal studies has demonstrated plausible biological mechanisms where the active form of vitamin D may influence n-6PUFA metabolism.

**25B 9:15 a.m. – 9:40 a.m.**

Comprehensive metabolomic and immological profiling of Asthma COPD Overlap (ACO)

**PRESENTING AUTHOR:** Nilanjana Ghosh, School of Medical Science and Technology, India

**CO-AUTHORS:** Priyanka Choudhury, Sushmita Roy Chowdhury, Rintu Banerjee, Parthasarathi Bhattacharyya, Koel Chaudhury

Asthma chronic obstructive pulmonary disease (COPD) overlap, termed as ACO, is a complex heterogeneous disease without any clear diagnostic or therapeutic guidelines. The pathophysiology of the disease, its characteristic features and existence as a unique disease entity remain unclear. The present study aims to determine whether ACO has a distinct metabolic and immunological mediator profile in comparison to asthma and COPD. The study was conducted on two different patient groups, the discovery and validation cohort. The discovery phase patient cohort consisted of (i) controls= 33 (ii) asthma=34 (iii) COPD=30 and (iv) ACO=35. For the validation phase (i) asthma=32 (iii) COPD=32 and (iv) ACO=40 were considered. Serum and exhaled breath condensates (EBC) were collected from all the subjects and characterized using nuclear magnetic resonance (NMR) spectrometry and gas chromatography mass spectrometry (GC MS) based metabolomics. The immunological mediator profiling (Th1, Th2, Th17 cytokines and soluble immune mediators) was assessed using quantikine ELISA kits and magnetic bead based multiplexing assays. Multivariate and univariate analysis of NMR and MS metabolomics of combined serum and EBC profiles indicated dysregulated metabolites in ACO patients when compared with both asthma and COPD, followed by validation in a fresh cohort of patients. Our findings suggest that ACO has an enhanced energy and metabolic burden associated when compared to asthma and COPD. ACO also exhibits altered inflammatory and immune profiles than any of the parent diseases. It is anticipated that our results will stimulate researchers to further explore ACO and unravel the pathophysiological complexities associated with the disease.

**25C 9:40 a.m. – 9:55 a.m.**

The relationship between the maternal metabolome and childhood asthma: results from the Vitamin D Antenatal Asthma Reduction Trial (VDAART)

**PRESENTING AUTHOR:** Mengna Huang, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, United States

**CO-AUTHORS:** Rachel S. Kelly, Su H. Chu, Priyadarshini Kachroo, Augusto A. Litonjua, Scott T. Weiss, Jessica Lasky-Su

Several prenatal and perinatal factors have been implicated in the development of childhood asthma, including maternal smoking, diet, and pregnancy complications. The maternal metabolome during pregnancy may therefore provide valuable mechanistic insights and novel hypotheses in asthma pathophysiology. This analysis included non-smoking pregnant women and their children who participated in VDAART, a randomized placebo-controlled trial to determine the effect of prenatal vitamin D supplementation on offspring asthma (ClinicalTrials.gov identifier: NCT00920621). Asthma outcomes were defined as physician-diagnosed asthma or recurrent wheezing by age 3 and 6 years. Metabolomic profiling in 775 mothers at 10-18 weeks gestation was conducted using ultrahigh-performance liquid chromatography-tandem mass spectrometry. After quality control 734 known metabolites remained. We assessed the prospective associations between individual maternal plasma metabolites and childhood asthma/wheezing using multivariable logistic regression models. In 719 mother-child pairs, top maternal metabolites associated with asthma/wheezing by age 3 were 2-aminoadipate (P-value=8.91e-4), tyramine O-sulfate (P-value=1.05e-3), and vanillactate (P-value=3.02e-3). Vanillactate and 2-aminoadipate were also associated with asthma/wheezing by age 6 (n=775, P-values=2.35e-3, 4.07e-3). Among 25 and 18 metabolites associated with asthma/wheezing by age 3 and 6 respectively (P-value<0.05), thyroxine, 3-methylcatechol sulfate, and theophylline were also common. 2-aminoadipate and thyroxine had positive, while others demonstrated inverse relations with the outcomes. We identified several prenatal metabolites associated with childhood asthma/wheezing. Previously linked to diabetes and atherosclerosis, 2-aminoadipate is a lysine oxidation product by myeloperoxidase in inflammation. Theophylline, a caffeine metabolite and known asthma therapy, has bronchodilatory and anti-inflammatory effects. Validation in similarly-designed independent cohorts is needed to confirm these associations.
SESSION 26: MODEL ORGANISMS

Thursday, June 27

8:45 a.m. – 10:00 a.m.

**26A Session Keynote**
**8:45 a.m. – 9:15 a.m.**

Can Stage-Specific Metabolites be Recovered from Mixed-Stage C. elegans Cultures?

**PRESENTING AUTHOR:** Arthur Edison, University of Georgia, United States

**CO-AUTHORS:** Sicong Zhang, Amanda O. Shaver, Brianna M. Garcia, Gonçalo J. Gouveia, Pam S. Kirby, Lauren M. McIntyre, Erik C. Andersen, Arthur S. Edison

The model organism Caenorhabditis elegans develops in ideal conditions through six distinct developmental stages over its approximately three-day life cycle. Under unfavorable conditions, it can enter an alternative developmental stage called dauer, which can persist for months and is specialized for dispersal to a more optimal environment. Each developmental stage is unique in terms of gene expression, cell number, cuticle structure, and metabolism. Methods are available to synchronize cultures in order to isolate stage-specific nematodes, but these methods are time-consuming and add extra steps with harsh conditions that can potentially disrupt normal development. Furthermore, synchronization complicates large-scale discovery metabolomics, as the choices are to either focus on one specific stage or perform a synchronization step for each given life-cycle stage thereby increasing handling time. We are using both natural diversity and targeted genetic mutations in C. elegans for a large-scale NIH Common Fund project to identify unknown metabolites enabled by genetics and quantum chemistry. In an attempt to enable experiments on mixed stage populations, we are developing methods that will deconvolve mixtures in both LC-MS and NMR data by leveraging a series of stage specific and mixed stage experiments. Our approach would allow us to identify C. elegans developmental stages within a mixed-stage population using a large-particle flow cytometer. Each stage can then be associated with LC-MS or NMR features or vice versa. We will present progress on this approach using the N2 reference strain and discuss how it can be extended to other genotypes.

**26B 9:15 a.m. – 9:40 a.m.**

Bringing together what belongs together – Bridging the Caenorhabditis elegans model organism database, genome scale model and metabolite databases

**PRESENTING AUTHOR:** Michael Witting, Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Germany

**CO-AUTHORS:** Jake P. N. Hattwell, Horst Joachim Schirra, Karen Yook, Keeva Cochrane, Claire O'Donovan

Despite considerable efforts, information on Caenorhabditis elegans metabolism, its genes, proteins and metabolites is currently scattered across different databases. The WormJam (short for Worm Jamboree) community is a world-wide community of researchers who aim to rectify this situation by constructing and curating a high-quality consensus genome-scale metabolic network (GSMN) of this important biomedical model organism. The resulting WormJam GSMN is currently one of the best curated metabolic models for C. elegans. WormJam collaborates with WormBase (www.wormbase.org), the premier repository for C. elegans genes, proteins, phenotypes, and related information. We have recently started to also add metabolites to this repository. The WormJam model uses ChEBI as primary information and deposition source for metabolite structures, and together with the WormJam community we have started towards full coverage of the C. elegans GSMN with metabolite structures. In addition, we are working on the integration of RheaDB to allow comparison of metabolic reactions between other organisms and C. elegans. Furthermore, we are collaborating with MetaboLights to link metabolomics raw and reference data. Here we present an application example using a case study on C. elegans sphingolipids and their analysis using UPLC-UHR-ToF-MS. We started from the correction and curation of sphingolipid-related reactions in WormJam as well as curation of structures, collection of reference MS and MS/MS. We are aiming to further develop the WormJam model and connected database as a comprehensive knowledge base for future investigations into the metabolism of C. elegans.

**26C 9:40 a.m. – 9:55 a.m.**

The use of mitochondrial metabolomics in discovering the molecular function of a mitochondrial membrane protein

**PRESENTING AUTHOR:** Daqiang Pan, Centre for Biological Systems Analysis, University of Freiburg, Germany

**CO-AUTHORS:** Caroline Lindau, Simon Lagies, Michael Rodamer, Nils Wiedemann, Bernd Kammerer

Yeast Saccharomyces cerevisiae SYM1 is an ortholog of the human MPV17 gene whose mutation causes mitochondrial DNA depletion syndrome. Sym1 protein is located in the inner mitochondrial membrane and its deletion results in impaired mitochondrial bioenergetic functions and morphological features under stress conditions. However, the functions of both Mpv17 and Sym1 have not been clearly characterized. Recently, compartment-specific metabolic alterations to mutations or inhibition of mitochondrial proteins were revealed by analyzing isolated mitochondria, opening new doors for uncovering the function of Sym1. Therefore, mitochondria and the corresponding cytoplasmic fraction of wild type and Δsym1 cells were isolated through differential centrifugation and subjected to metabolomic analysis. TCA cycle intermediates were accumulated overall in Δsym1 cells. This correlates with the results of Dallabona et al., which showed severe OXPHOS defects of Δsym1 under stress conditions. Meanwhile, accumulated saccharopine and reduced lysine suggested an interrupted lysine biosynthesis, which was proved by incubating yeast cells without the supply of lysine. Interestingly, pyrimidine biosynthesis intermediates, carbamoyl-aspartate and orotic acid, were reduced in Δsym1 cells. This situation became worse when the growth temperature was shifted, after incubation for eight hours, from 30 °C to 37 °C for eight hours, indicating that sym1 may play a role in pyrimidine biosynthesis. This is the first time that metabolomics was applied to determine the molecular function of the mitochondrial inner membrane protein sym1, which gives new aspects in understanding its function.
## SESSION 27: GENOME-SCALE MODELING

Thursday, June 27

8:45 a.m. – 10:00 a.m.

**27A Session Keynote**

8:45 a.m. – 9:15 a.m.

Computational modelling of host-microbiome co-metabolism

**PRESENTING AUTHOR:** Ines Thiele, National University of Ireland, Ireland

Computational modelling of human and microbial metabolism has gained increasing attention for phenotypic characterization. Such modelling is achieved by assembling in a bottom-up manner a high-fidelity computational representation of an organism's metabolic network based on genomic, biochemical, and physiological data. We have developed a semi-automated pipeline for the assembly of high-fidelity microbial metabolic networks and applied this pipeline to generate a collection of more than 800 gut microbial metabolic networks. We can now combine these metabolic networks, e.g., based on metagenomic data, to predict emergent metabolic capabilities of the microbial community and their potential effect on the human host. To that end, we built whole-body metabolic models of a male (deemed Harvey) and a female (deemed Harvetta), which describe accurately the metabolism occurring in 28 organs. Importantly, these whole-body models can be expanded to include the strain-resolved metabolic models of gut microbes. I will demonstrate how different microbial composition leads to differences in host metabolism, such as the capability to produce important neurotransmitters in the brain and flux through liver enzymes, with implications for the gut-brain axis as well as for microbiome-mediated liver toxicity. The predictions were consistent with our current understanding but also highlighted that different microbiota composition can lead to high inter-person variability. I envisage the microbiome-associated whole-body metabolic models will usher in a new era for research into causal host-microbiome relationships and greatly accelerate the development of targeted dietary and microbial intervention strategies.

**27B 9:15 a.m. – 9:40 a.m.**

Metabolic footprint of Parkinson's Disease: integration of patient-derived X-omics data with a human genome-scale model.

**PRESENTING AUTHOR:** Agnieszka Wegrzyn, LACDR, Leiden University, Netherlands

**CO-AUTHORS:** Agnieszka Wegrzyn, Edinson Lucumi, Alida Kindt, Cornelius Willacey, German Preciat, Jennifer Modamio Chamarro, Zhi Zhang, Evan G. Williams, Rashi Halde, Javier Jarazo, Paul Wilmes, Enrico Glaab, Jens Schwamborn, Amy Harms, Thomas Hankemeier, Ronan M.T. Fleming

The exact molecular mechanism of Parkinson's disease (PD) is currently unknown. However, it is believed that metabolic malfunctions play an essential role in the development of PD. Several genetic risk factors linked to bioenergetic alterations were identified, including mutations in a mitochondrially targeted, neuroprotective serine/threonine protein kinase PTEN-induced kinase (PINK1). However, the link between PINK1 mutations and the metabolic deregulation that leads to the development of PD remains mostly unknown. Here, we explore the metabolic footprint of a PINK1 mutation by creating a PINK1-specific metabolic model based on integrated patient-derived x-omics data. To provide patient-specific constraints of the PINK1-Q456X mutation for the model, we generated transcriptomic (RNAseq), untargeted proteomics, and quantitative exometabolomic (targeted mass spectrometry) data from in vitro cultures of patient iPSC-derived dopaminergic neurons carrying this mutation. Each PINK1-Q456X neuronal line was paired with its isogenic control, in which the PINK1 gene was corrected. Additionally, cell lines derived from healthy volunteers were used for comparison. With this x-omics data, we generated constraint-based, genome-scale, patient-specific in silico models of dopaminergic neuronal metabolism affected by the PINK1 mutation (iPINK1). Furthermore, we created patient-specific control models reflecting the metabolism of isogenic controls (iPINK1iso) and healthy volunteers (iPINK1ctrl). Our models are being used to predict targets for reducing mitochondrial dysfunction. We will check which non-trivial perturbations to reaction rate(s) can compensate for the effect of mutations in monogenic PD patients, or act to improve dysfunctional mitochondrial phenotypes.

**27C 9:40 a.m. – 9:55 a.m.**

Genome-wide metabolic modeling of human CD4+ T-helper cells differentiation unraveled the relative importance of ceramides

**PRESENTING AUTHOR:** Partho Sen, Postdoctoral Researcher, Finland

**CO-AUTHORS:** Partho Sen, Alex M Dickens, Ubaid Ullah, Syed Bilal Ahmad Andrabi, Mohd Moin Khan, Tuomas Lindeman, Esko Kemppainen, Tanja Buchacher, Omid Rasool, Tuulia Hyötyläinen, Riitta Lahesmaa, Matej Oresic

T-helper (Th) cells play a pivotal role in cell-mediated immunity. During the development, T cells undergo metabolic remodeling that is essential for orchestrating the action of other immune cells. In order to understand global metabolism during T-cell development, we developed genome-scale metabolic models (GEMs) for human Th1, Th2 and Th17 subsets and T-regulatory cells (iTreg)1. Meta-analysis of T-cell specific human transcriptomics datasets have identified 72 novel metabolic genes, corresponding to 355 reactions spanning various metabolic pathways. Reporter metabolites and pathway overrepresentation analysis suggested that T-cell activation induces gluconeogenesis, glutaminolysis, and lipid biosynthesis. Moreover, ganglioside (GA1, GMb) and N-acetylneuraminate (NANA) associated with sialyl-T antigen were significantly up-regulated in Th17 cells at 72 hours of initiation, while the glucosyl-, lactosyl- and galactosyl ceramides were down-regulated. On contrary, such trends were either reversed or absent in iTregs at this time-point. Our findings suggest that, ceramides are involved in the metabolic regulations and functioning of T-cells. It was also found that, Th subsets exhibit unique metabolic phenotype, already during early stages (72 h) of specification, thus playing a central role in guiding the fate of the cells. These results are being validated by Liquid Chromatography and Mass spectrometry (LC-MS)-based targeted metabolomics experiments. The findings from this study, provide a basis for modulation of human Th subsets crucial for immune responses under metabolically aberrant conditions and in immune-mediated disorders.
SESSION 28: MICROBIOME

Thursday, June 27

10:45 a.m. – 12:00 p.m.

28A Session Keynote
10:45 a.m. – 11:15 a.m.

Global Chemical Impacts of the Microbiome Include Novel Conjugated Bile Acids that Stimulate FXR

PRESENTING AUTHOR: Robert Quinn, Michigan State University, United States

CO-AUTHORS: Alexei Melnik, Alison Vrbanac, Zsolt Bodai, Hera Vlakamis, Ting Fu, Julian Avila-Pacheco, Morgan Panitchpakdi, Mingxun Wang, Ron Evans, Manuela Raffatellu, Curtis Huttenhower, Sarkis Mazmanian, Rob Knight, Pieter Dorrestein

A mosaic of cross-phyla chemical interactions occurs between all metazoans and their microbiomes. These microbial residents in humans are increasingly well characterized, but we have yet to elucidate the breadth of the chemical diversity the microbiome contributes. We used untargeted LC-MS/MS based metabolomics and the mass spectrometry database GNPS to assess the global metabolite differences between germ-free (GF) and colonized mice. Of the 7,913 molecules detected across 29 murine organs, 14.7% were unique to SPF. Unique microbial compounds included bile acids conjugated with the amino acids phenylalanine, tyrosine and leucine, which represent a new tertiary group of bile acids produced by the microbiome that have eluded discovery in the 170 years of research on bile chemistry. Culturing human gut isolates revealed that Clostridium bolteae was responsible for their production. These molecules were found in the upper GI tract of mice and elevated in abundance when fed high fat. Searching GNPS showed that they are also present in humans and elevated in individuals with inflammatory bowel disease (IBD). These novel conjugates strongly agonize the human FXR receptor, which is a global regulator of bile acid metabolism. Unlike the host produced glycine and taurine conjugates, these novel molecules could not be deconjugated by the microbiota, making their action on the FXR constitutive. FXR agonism in vivo reduced the overall production of bile, making these molecules microbial manipulators of bile acid metabolism. The discovery of these molecules opens up a new era in bile acid research linking these novel conjugates with human disease.

28B 11:15 a.m. – 11:40 a.m.

Exploring the microbiota-host epigenetics axis in female and male germ-free and conventional mice

PRESENTING AUTHOR: Joan Miró Blanch, Metabolomics Platform, IISPV & Department of Electronic Engineering, Universitat Rovira i Virgili, Spain

CO-AUTHORS: Jordi Capellades, Alexandra Junza, Magdalini Serefidou, Claire Maudet, Aurélie Balvay, Pau Gama-Perez, Ignasi Forné, Pablo M. Garcia-Roves, Axel Imhof, Oscar Yanes

Histone modifications are major regulators of the epigenetic machinery, due to their ability to modulate gene expression, DNA repair and chromatin structure. These post-translational modifications (PTMs) are dynamically regulated by specific modifying enzymes whose activities require metabolites that either serve as substrates, cofactors or act as activators/inhibitors. The level of these metabolites depend on host metabolism and environmental factors, including the metabolic activity of gut microbiota. Here, liver tissue from male and female germ-free (n=20) and conventional (n=20) mice has been studied to gain new knowledge on the epigenetic regulation at the interplay between host and gut microbiota metabolites. To do this, we have implemented a targeted metabolomic analysis by LC-QqQ MS covering >30 epigenetically relevant metabolites playing a regulatory role in histone acetylation, methylation, phosphorylation, ADP-ribosylation, and N-acetylglucosamination reactions. At the same time, we have quantified histone PTMs by LC-MS/MS in data dependent acquisition mode. Remarkably, we observed that S-Adenosyl-Methionine (SAM) is altered in the absence of microbiota and this highly correlates with changes in lysine methylation status of histones H3 and H4. These results were further validated in diet-induced obese mice presenting changes in the gut microbiota composition. Furthermore, ongoing RNAseq experiments will hopefully reveal alterations in the liver transcriptional profile associated with the absence (germ-free) or dysbiosis of the microbiota induced by a high fat diet.

28C 11:40 a.m. – 11:55 a.m.

Individual Variations in Plasma Metabolites are Driven by Diet, Genetics and Gut Microbiome

PRESENTING AUTHOR: Lianmin Chen, University Medical Centre Groningen, Netherlands

CO-AUTHORS: Daria V. Zhernakova, Mihai G. Netea, Folkert Kuipers, Cisca Wijmenga, Alexandra Zhernakova, Jingyuan Fu

Plasma metabolome and its inter-individual variation underlie individual's susceptibility of various complex diseases. Diet, genetics, and the gut microbiome are determinants of human metabolic status. However, their relative contributions to variation in plasma metabolome remain elusive. Here, we present a comprehensive host-microbe-diet interaction analysis on over 1000 plasma metabolites in a population-based Lifelines-Deep cohort (n=1,440), for each individual we had completed information on the gut microbial taxonomic and functional composition, genetic background, blood metabolites, dietary factors, medication and clinical phenotypes. Our study found diet, genetics and gut microbiome could explain 9%, 8% and 14% of variation respectively. Moreover, medication explained 4% and host physiological status could explain 10%. These factors together contributed 39% of variation in plasma metabolome. On individual metabolite level, we reported 88 associations to genetics, 369 to the gut microbial species, 7884 to microbial pathways and 261 to dietary factors at FDR<0.05. Notable, 61 metabolites were associated to all of them, indicating host-microbe-diet interactions. These metabolites are enriched for lipids, amino acids, carbohydrates, bile acids and fatty acids, which in turns can affect host health and disease. Notable, some microbial metabolites synthesized or modulated by the gut microbiome are linked not only to human derived metabolites but also linked to host immune profile. Taken together, this study reveals important evidence for a significant role of the gut microbiome in host metabolism and its interaction with diet and host genetics, providing clues for future applications in personalized medicine.
## SESSION 29: PLANT APPLICATIONS 2

Thursday, June 27

10:45 a.m. – 12:00 p.m.

**29A Session Keynote**
10:45 a.m. – 11:15 a.m.

A novel plant-microbiome co-culturing system reveals key associations of specific metabolites with plant growth and stress tolerance

**PRESENTING AUTHOR:** Sanjay Swarup, National University of Singapore, Singapore

**CO-AUTHORS:** Gourvendu Saxena, Ee Yong Lian, Pavagadhi Shruti, Miko Poh Chin Hong, Yeap Yoon Ting

Plants coexist with microbes as holobionts, sharing mutually beneficial functions, which can be engineered to produce ecologically and environmentally favorable outcomes. The rhizosphere microbial community, which occupies the niche developed by the gradients of root exudates in the rhizosphere region is of particular interest due to its probable direct role in providing specific factors for plant growth. However, the lack of a model rhizosphere microbial community and its metabolite exchanges with the host has limited the much needed mechanistic understanding of plant-microbe interactions in the rhizosphere. To fill this gap, we have developed a novel plant holobiont gnotobiotic system with specific characteristics of (i) co-culturing of model plant, Arabidopsis thaliana or related Brassica leafy vegetables, with a highly complex microbial community of hundreds of taxa; (ii) easy real-time phenotyping of plant growth; (iii) metabolites recovery from root surface or root-microbiome interface and (iv) microbiome recovery from the co-culture system. Live exudation from plants supports a highly complex microbiome community of several hundred taxa and recovery of highly complex metabolites mixture. High Resolution and Accurate Mass –mass spectrometry using an Orbitrap system led to the identification of more than 15,000 de-isotoped molecular features. Using this system, we show a very specific plant growth effect by the enriched rhizosphere microbial community on the plants through different distinct metabolic pathways, when compared with the bulk-soil microbial community. The mechanistic understanding from this research framework can be used on specific crops to enhance the yields without adding carbon or water footprint to the system.

**29B 11:15 a.m. – 11:40 a.m.**

An untargeted LC-MS based work-flow for the structural characterization of biological polyesters

**PRESENTING AUTHOR:** Rebecca Dauwe, Université de Picardie Jules Verne, France

**CO-AUTHORS:** Benjamin Thiombiano, Roland Molinié, Paulo Marcelo, Eric Gontier, François Mesnard

We developed an LC-MS based strategy to characterize fragments of the lignin macromolecule, a complex phenolic polyester that accumulates in flax seed integuments. The polyester was subjected to a dynamic alkaline hydrolysis process that was stopped after a series of increasing reaction times, and the hydrolysates were analyzed by LC-MSn. Analysis of the final hydrolysates led to the identification of 31 monomeric subunits. For the characterization of the partial hydrolysates, we show that the annotation of pairs of related LC-MS features, based on m/z differences, strongly facilitates their characterization. Using self-organizing maps, we first preselected as candidate ester-containing compounds those features that transiently appeared during the dynamic hydrolysis process. Among all possible pairs of the preselected features, we revealed 46 overrepresented m/z differences that corresponded to the addition of identified macromolecule monomers or of theoretically possible oligo-esters built of two or three monomeric units. In order to reveal the features that represent different fragments of the same lignan macromolecule, a candidate substrate-product pair network connecting the selected features by the annotated overrepresented m/z differences was built. The network information was then combined with the interpretation of MSn data to elucidate the structures of the saponification fragments. In total, 120 distinct oligo-esters, consisting of up to 6 lignan macromolecule monomers could be characterized. These results allowed us to further elaborate the existing structural model of the lignan macromolecule. Our network approach shows promising to tackle the structural characterization of different types of complex plant polyesters, such as suberin and cutin.

**29C 11:40 a.m. – 11:55 a.m.**

NMR-MS metabolomics reveals sulfonation in the Salicaceae

**PRESENTING AUTHOR:** Clarice Noleto-Dias, Rothamsted Research, United Kingdom

**CO-AUTHORS:** Claudia Harflett, Jane L. Ward, Michael H. Beale

The Salicaceae family is characterised by the presence of phenolics, including the glycosides of the salicinoid sub-group and different types of flavonoids. Rothamsted Research is home to the National Willow Collection, comprising 1500 different accessions. In addition, large scale mapping populations have been developed. A metabolomics screen of a diversity panel comprising mapping population members and their parental lines suggested that a particular population (MpF) was dominated by metabolites not observed in other Salix species. Fractionation via HPLC was performed to isolate all the novel compounds present in the sample. Five sulfated compounds were isolated and their structures elucidated by LC-HRMS-MS and 1D and 2D-NMR. Four compounds were found in leaf and stem tissues of S. alberti x S. integra x S. suchowensis hybrid (NWC901), a parent of MpF, and these were characterised as taxifolin-7-sulfate, dihydrokaempferol-7-sulfate, eriodictyol-7-sulfate and narigenin-7-sulfate. Although sulfation of natural products is not rare, and occurs often in mammalian metabolism, most examples from the plant world concern sulfated flavonoids from flavonol and flavone subclasses, different to the flavanonols and flavanones reported herein. An additional compound, salicin-7-sulfate, was also identified in the LC-MS datasets of stem tissue samples harvested at the dormant stage of some of the 86 pure Salix genotypes. Among these lines, no correlation between the amount of salicin and its sulfated form could be detected. We will present data on compounds that have not been previously described in plants and discuss the implications of their presence in willow, a plant traditionally used in herbal medicine.
## SESSION 30: METABOLITE IDENTIFICATION 2

Thursday, June 27

10:45 a.m. – 12:00 p.m.

**30A Session Keynote**
10:45 a.m. – 11:15 a.m.

Correlation-based deconvolution (CorrDec) method for data-independent acquisition mass spectrometry

**PRESENTING AUTHOR:** Ipputa Tada, Department of Genetics, SOKENDAI (Graduate University for Advanced Studies), Japan

**CO-AUTHORS:** Romanas Chaleckis, Hiroshi Tsugawa, Isabel Meister, Pei Zhang, Craig E. Wheelock, Masanori Arita

Metabolite identification is still a major challenge in untargeted metabolomics. Data-independent acquisition mass spectrometry (DIA-MS) is essential for information-rich and reproducible analysis of metabolome, but the acquired full-scan MS2 spectra are highly complex and pose harder challenges for annotation and identification. We have developed a new deconvolution method (CorrDec) that exploits the correlation between peak intensities of precursor and fragment ions in multi-sample studies measured with All Ion Fragmentation (AIF). Its main advantage is the discrimination of completely co-eluting, low-abundance compounds; this is the first software approach that systematically disentangles clean MS2 spectra from full-scan AIF data. The CorrDec was implemented in our MS-DIAL software (version 3.32 or later) and its performance was rigorously assessed with the original, retention-time based MS-DIAL deconvolution (MS2Dec) using a dilution series of chemical standards and biological samples. Both methods function in complement, and the benefit of CorrDec is extraction of cleaner, i.e., more library-matching MS2 spectra than MS2Dec when multiple samples are available. In this presentation, we report detailed performance comparison of both deconvolution methods and our randomized assessment using biological samples to estimate the required number of measurements for CorrDec. We also introduce interpretation of deconvoluted MS2 spectra of marginally identifiable metabolites, using co-eluting betaines as a model case.

**30B 11:15 a.m. – 11:40 a.m.**

Evaluation of molecular ionization propensities in different ionization modes: providing evidence for the presence of small molecules in synthetic blinded samples

**PRESENTING AUTHOR:** Jamie Nunez, Pacific Northwest National Laboratory, United States

**CO-AUTHORS:** Sean Colby, Thomas Metz, Justin Teeguarden, Ryan Renslow

For non-targeted metabolomics analysis, the relative ionization propensities of molecules analyzed using different ion sources (e.g. electrospray, ESI; atmospheric pressure photoionization, APPI) is not well understood. Improved understanding of ionization propensities would offer many advantages in metabolomics, such as (i) a priori selection of ionization modes based on suspected sample composition, (ii) the ability to reduce the number of candidate structures during data analysis by removing those less likely to ionize, and (iii) a reduced false discovery rate and increased confidence in identifications. Here, we will discuss a blinded analysis of synthetic chemical mixtures, each containing up to hundreds of unique compounds, as part of the U.S. EPA's Non-Targeted Analysis Collaborative Trial (ENTACT). We report how different ionization modes contributed to overall identifications, as well as how certain chemical properties (e.g., pKa, LogP, molecular mass, ring-count) and chemical substructures (e.g., heterocyclic rings and carboxyl, carboxamide, and phosphino groups) influence ionization propensities. For example, several chemical properties were found to be statistically significantly different for compounds identified using ESI or APPI, and in positive or negative ionization modes. Furthermore, we clustered compounds based on their chemical properties, chemical class, and chemical substructures, and found that certain properties and substructures were highly correlated with detection in specific ionization modes, while chemical class, derived from an automated ontology (ClassyFire) did not provide strong discriminating information. While similar analyses have been performed on a small scale in the past, our fully automated approach facilitated a large-scale analysis and provides a foundation for future studies.

**30C 11:40 a.m. – 11:55 a.m.**

Improved oxylipins and fatty acids identification by using LC-DTIM-MS

**PRESENTING AUTHOR:** Sonia Liggi, Department of Biochemistry and Cambridge Systems Biology Centre, University of Cambridge, United Kingdom

**CO-AUTHORS:** Christine Hinz, John Fjeldsted, Julian L. Griffin

The use of liquid chromatography coupled with drift tube ion mobility and mass spectrometry (LC-DTIM-MS) can help the characterization and identification of lipid species, reflecting the additional dimension provided by ion mobility which can improve separation of the numerous structural isomers in these molecular classes. Nonetheless, the analysis of oxylipins is particularly challenging given their physiological low abundance in biological samples and the narrow mass range occupied by this lipid category. To overcome these limitations, we developed a combined analytical-computational method for the analysis and identification of oxylipins and their precursor fatty acids. Herein, we focus on presenting the computational part of the workflow. More specifically, accurate mass, collision-cross section values in nitrogen (DTCCSN2) and retention times of 47 oxylipins and fatty acids standards were obtained after triplicate acquisition on a reversed-phase LC-DTIM-MS workflow, and integrated in an internal library subsequently used for the identification of these compounds in biological samples. Aside from directly identifying oxylipins and fatty acids, we were also able to flag species as similar to those in the internal library. These flags not only reduce the number of annotations from external databases, providing a lead for further characterization analyses, but also guide discovery studies of potentially novel species. The method was applied to several datasets of biological samples, such as Salmonella enterica serovar Typhimurium infected murine bone-marrow derived macrophages and thrombin activated human platelets, providing results in agreement with the literature and improving the identification of features otherwise annotated with a vast number of compounds.
Poster Abstracts

<figure><img src="image_29.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.

*AWARD WINNERS

BIOMEDICAL

**P-1** The impact of the Healthy New Nordic diet on the human urine metabolome as measured by 1H-NMR spectroscopy

**PRESENTING AUTHOR:** Alessia Trimigno, University of Copenhagen, Denmark

**CO-AUTHORS:** Bekzod Khakimov, Søren Balling Engelsen

More than a decade ago, chefs and scientists designed the New Nordic diet (NND). This diet was based on sustainable, local and nutritious foods. It mainly consisted in vegetables, fruits, berries, nuts, fish, shellfish and game meat. NND was proved beneficial on overweight people, i.e. decreasing body weight, reducing glycaemia, lowering blood pressure, and improving blood lipids. In this study, we investigated how the healthy NND affects the human urine metabolome and compared it with the effect of the Average Danish Diet (ADD). Urine samples from 142 centrally obese Danes were collected at baseline, after 6 months and 12 months of intervention. Subjects were randomly assigned to ADD or NND. Urine samples were analyzed through untargeted 1H-NMR spectroscopy and the acquired spectra were converted into a metabolite table using the novel Signature Mapping (SigMa) approach. The urine metabolite table was scrutinized using multivariate data analysis methods to reveal the impact of the different study design factors including diet, season, gender, and bodyweight change. NND samples revealed higher concentrations of glycine, betaine, glucose, TMAO and creatinine, whilst ADD urine had greater levels of tartrate, dimethyl sulfone and propylene glycol. The latter was also found to be associated in the NND group with the homeostatic model assessment for insulin resistance (HOMA). Results from this study corroborate previous information on the NND, indicating different effects on the metabolism of proteins and carbohydrates, and help in better understanding its actual impact on human health (e.g. glycaemia, inflammation) and on the gut microbiota metabolism.

**P-2** Environmental cadmium exposure disrupted mitochondrial metabolome in human and mouse lungs

**PRESENTING AUTHOR:** Young-Mi Go, Emory University, United States

**CO-AUTHORS:** Matthew R. Smith, Xin Hu, Jolyn Fernandes, Michael Orr, Doug Walker, David Neujahr, Dean P. Jones

Cadmium (Cd) causes adverse health effects from occupational exposures and cigarette smoking. Lower level of environmental Cd exposure, principally from food, is a global health concern because of the long biological half-life of Cd (10-30 years) in humans and animals. Despite Cd toxicity at high dose exposures being well documented, the impacts of Cd exposures at low levels through dietary intake has only recently been characterized. Our previous study showed that lung Cd burden found in non-smoker's lung caused changes in the mouse lung metabolome with effects on airway reactivity, glycolysis and lipid metabolism, inflammation and profibrotic signaling. Our data further showed potentiated adverse reaction to H1N1 influenza virus and respiratory syncytial virus and worsened microbiome disruption by high-fructose diet. In the current study, we examined the effects of Cd on lung mitochondrial metabolome using ultrahigh-resolution mass spectrometry-based high-resolution metabolomics (HRM). Mitochondria (250 mg) isolated from lungs were analyzed for metabolome and metabolic pathway by HRM, and concentrations of Cd and other metals by Inductively Coupled Plasma Mass Spectrometry. The results showed that Cd caused alterations in large numbers of mitochondrial metabolites including fatty acids, carnitines and CoA, and disrupted fatty acid oxidation and energy metabolism. The results suggest that Cd accumulation by dietary exposure could be a potential pulmonary health risk involving disruption of mitochondria as a central mechanism in lung, specifically in fatty acid and energy metabolism and enhanced inflammation by mitochondrial H2O2 signaling.

**P-3** Integration of proteomics and metabolomics data to stratify severe septic shock patients

**PRESENTING AUTHOR:** Manuela Ferrario, Politecnico di Milano, Italy

**CO-AUTHORS:** Alice Cambiaghi, Eliandre de Olivera, Laura Brunelli, Roberta Pastorelli

In this work, we examined plasma metabolome and proteome in patients with severe septic shock enrolled in the multicenter ALBIOS study (Albumin Italian Outcome Sepsis study, NCT007071225). The objective was to identify changes in the levels of metabolites involved in septic shock progression and to integrate this information with the variation occurring in proteins. Mass spectrometry based targeted metabolomics and untargeted proteomics allowed us to quantify absolute metabolites concentration and relative proteins abundance. We computed the fold change D7/D1 to take into account their variation from day 1 (D1) to day 7 (D7) after shock diagnosis. Patients were divided into two groups according to 28-day mortality. Two different elastic net logistic regression models were built: one on metabolites only and one on metabolites and proteins. Linear Discriminant Analysis and Partial Least Squares Discriminant Analysis were also implemented. A filter strategy was adopted to reduce the number of features. All the obtained models correctly classified the observations in the testing set. Our findings confirmed that non-survivors have different trend in plasma levels of lipid species in comparison to survivors, in line with previous works. Our approach showed that the proteins decisive in stratifying the patients are those related to the inflammatory response and the coagulation cascade, which are known to play an important role in septic shock progression, thus confirming the feasibility and robustness of our integrative approach. Integrating metabolomics data with proteomics one enabled to highlight key features associated with the outcome.
<figure><img src="image_30.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.

*AWARD WINNERS

BIOMEDICAL

P-4 **New insight in Metabolomics based study of Age Related Macular Degeneration (AMD): Lipoprotein profile and patients follow-up**

PRESENTING AUTHOR: Matthieu Schoumacher, Uliege (CIRM), Belgium

CO-AUTHORS: V. Lambert, S. Hansen, J. Leenders, B. Govaerts, B. Pirotte, J.-M. Rakic, A. Noël and P. de Tullio

Age-related macular degeneration (AMD) is common disease and leading causes of vision loss among people aged 50 and older. Late-stage AMD (called exudative) is characterized by choroidal neovascularization (CNV) and results in complete loss of central vision acuity leading to severe visual impairment and legal blindness. Currently, AMD diagnosis relies on ophthalmologic exams and treatments of the exudative form using anti-angiogenic drugs targeting vascular endothelial growth factors (VEGF). Despite these advances, the identification of therapeutic treatments and related biomarkers are essentials. In this study, we applied a NMR-based metabolomics approach on a cohort of AMD patients and on a laser-induced murine CNV experimental model that mimics the pathology angiogenesis's development phase. Sera from controls and AMD patients (in active and non-active pathology's phases) and from induced and non-induced mice have been collected and submitted to a metabolomics study, using a multivariate approach. This approach allows differentiation between active and non-active AMD patients and between laser-induced and the control mice groups. Moreover, the discriminating spectral zones are the same in both human and mice's models, leading to the emergence of putative biomarkers of the exudative AMD. Among those, lipoprotein profile is interesting while some studies highlighted HDL cholesterol and oxidized LDL with early and para-inflammatory AMD stages. Our primary studies show similar evolution in lipoprotein profile through the different human and mice' groups. These data suggest that investigate lipoprotein profile could be the turning point in the pathologic process's comprehension occurring during the apparition and/or the development of pathologic CNV process.

P-5 **Confirming the key role of glutathione in the mechanism of drug resistance to artemisinin-based antimalarials**

PRESENTING AUTHOR: Dovile Anderson, Monash University, Australia

CO-AUTHORS: Ghizal Siddiqui, Amanda De Paoli, Darren J. Creek

Malaria treatment is reliant on artemisinin and its analogues in combination with partner drugs. Emerging resistance of Plasmodium falciparum parasites to artemisinin-based combination therapies (ACTs) reduces clinical effectiveness and threatens global malaria control efforts. Therefore investigations of the mechanisms of resistance are urgently required. It has been shown that slow parasite clearance following artemisinin treatment is associated with mutations in the PfKelch13 gene. Metabolomics analysis of these PfKelch13-mutant parasites has revealed increased levels of glutathione (GSH) and gamma-glutamyl cysteine compared to the artemisinin-sensitive line. GSH is known to play a pivotal role in anti-oxidative defence and other cellular processes within the parasite. In this study, the role of GSH in PfKelch13-mediated artemisinin resistance was investigated by inhibiting GSH biosynthesis pathways. Inhibition of GSH biosynthesis was achieved by pre-incubating resistant parasites with buthionine sulphoximine (a gamma-glutamylcysteine synthetase inhibitor) and sulfasalazine (a cysteine transport inhibitor), which restored sensitivity towards artemisinin to levels comparable to sensitive lines (40% survival decreased to 18%, p < 0.05). A targeted LCMS assay was developed and validated to measure the levels of free and oxidised thiols in parasites (sensitive and resistant) following GSH depletion. These findings give further insight into parasite detoxification mechanisms and confirm the key role of GSH metabolism in PfKelch13-mediated artemisinin resistance.
<figure><img src="image_31.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.

*AWARD WINNERS

BIOMEDICAL

P-6

Metabolomics analysis of human serum for population-based characterisation of ageing in men

PRESENTING AUTHOR: *Dakshat Trivedi, Mancehster Institute of Biotechnology, University of Manchester, United Kingdom*

CO-AUTHORS: *Fredrick Wu, Roy Goodacre*

With increasing life expectancy in most developed countries, it is becoming essential that the promotion of healthy ageing is part of public health objectives. However, relatively little is known about the hormonal transitions in men compared to female at the onset and progression of ageing (Lee et al., 2009). In particular, the changes in the human metabolome during this phase of life are relatively under-studied. Metabolomics is aimed at measuring the totality of the metabolites within a particular biological system (Goodacre et al., 2004) be it blood, urine or cells. To determine the differentiating classes of metabolites of ageing men, serum from 384 ageing males of different ethnic origin i.e. South Asian (SA) (n=118), African Caribbean (AC) (n=118) and White European (WE) (n=118) were chosen for spectroscopic analysis. Subjects' BMI values (+/- 2) and age (+/- 1 year) were matched prior to analysis. 300uL serum was analysed with Raman spectroscopy under 785nm laser at 100% laser power, centred at 1500cm⁻¹, 10s exposure time and 6 accumulations acquired per sample. 1µl serum was dried and analysed with Fourier Transformed Infrared (FT-IR) Spectroscopy in transmission mode, with 64 spectral scans co-added and averaged between the spectral range of 4000cm⁻¹- 600cm⁻¹ with 4cm⁻¹ resolution. Multivariate statistical analysis showed both spectroscopic techniques indicating a clear separation between subjects based on their ethnic origin. Significant clustering was seen between WE to SA and AC combined. PC-DFA loadings demonstrated vibrations and spectral features highlighting differences in metabolites of fatty acids and other lipids.

P-7

Role of Metabolomics in Age-related Macular Degeneration

PRESENTING AUTHOR: *Deeba Husain, Mass Eye and Ear, Harvard Medical School, United States*

CO-AUTHORS: *Ines Lains, Wonil Chung, Rachel S Kelly, John B Miller, Rufino Silva, Demetrios G Vavvas, Ivana K Kim, Jessica Lasky-Su, Liming Liang, Joan W Miller*

**Purpose:** Age-related macular degeneration (AMD) is the leading cause of blindness worldwide. This work aimed to assess and validate plasma metabolomic profiles of AMD and its severity stages, to better understand AMD pathogenesis. **Methods:** Prospective, cross-sectional study in two populations (Boston, United States and Coimbra, Portugal), including AMD subjects and controls. Fasting blood samples were analyzed using ultra-performance liquid chromatography and high-resolution mass spectrometry (Metabolon Inc). For each study site, logistic regression analysis was performed to identify metabolites linked to AMD as compared to controls (per subject model), and proportional-odds cumulative logistic regression models were built to assess metabolites varying across disease stages (both eye model). Liptak-Stouffer weighted Z-method was used for Meta-analysis. The predictive ability of the significantly identified metabolites was assessed using receiver operating characteristic (ROC) curve analysis, and their biological relevance performing pathway analysis (MetaboAnalyst). **Results:** We included 491 subjects; 196 (76% AMD, 24% controls) from Boston and 295 (82% AMD and 18% controls) from Coimbra. Meta-analysis revealed that, controlling for confounding factors and false discovery rate, 28 plasma metabolites differed significantly between AMD patients and controls; and 67 were significantly different across different disease stages. Pathway analysis revealed a significant enrichment of glycerophospholipids, purine, taurine and hypotaurine, and nitrogen metabolites (p< 0.04). **Conclusion:** AMD patients present a distinct plasma metabolomic profile, that varies according to disease severity. These findings contribute to the understanding of important pathways involved in AMD, support the future development of biomarkers and may help in developing individualized treatment for this blinding condition.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

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BIOMEDICAL

P-8 Exercise is associated with elevated levels of 10-PAHSA and improved adipose tissue functions in elderly women

PRESENTING AUTHOR: Marina Oseeva, Institute of Physiology of the Czech Academy of Sciences, Czech Republic

CO-AUTHORS: Marie Brezinova, Tomas Cajka, Marek Stepan, Klara Dadova, Michaela Siklova, Martin Rossmeisl, Ondrej Kuda

The studies performed with elderly people suggest that physical activity and/or dietary interventions may improve disturbances of lipid and carbohydrate metabolism. We aimed to explore the possible synergistic effect of exercise training (ET) and supplementation of a low dose of omega-3 polyunsaturated fatty acids (Omega-3), which could enhance the beneficial metabolic effects of ET on adipose tissue (AT). Fifty non-obese elderly women (70 ± 4 years, BMI: 27 ± 4) were divided into two groups and underwent combined aerobic and resistive training (3 times a week, supervised) with or without Omega-3 supplementation (2.5 g of Calanus® oil per day) for 4 months. Before and after the interventions, insulin sensitivity was determined by hyperinsulinemic-euglycemic clamp, and samples of blood and subcutaneous AT were collected for both targeted and untargeted metabolipidomic analyses. Serum metabolomics and lipidomics revealed that Calanus oil served as a source of Omega-3, improved insulin sensitivity, but did not change the lipidomic profile of subcutaneous AT and production of pro-resolving lipid mediators. Surprisingly, levels of 10-PAHSA (palmitic acid ester of hydroxystearic acid) and several other related metabolites were strongly induced (≈5-times) by the ET. PAHSA levels in serum and AT negatively correlated with AT insulin resistance parameters calculated from fasting insulin and free fatty acids levels. Our results suggests that insulin-sensitizing effects of PAHSAs might contribute to the beneficial effects of ET on the metabolism of AT in elderly women.
This project was supported by the Czech Ministry of Health 16-29182A, Czech Science Foundation GJ17-10088Y, and Calanus AS, Norway

P-9 Metabolomics of Poor Respiratory Health with Aging

PRESENTING AUTHOR: Haley Bayne, Brigham and Women's Hospital, United States

CO-AUTHORS: Rachel S. Kelly, Avron Spiro III, David Sparrow, Pantel Vokonas, Claudia Langenberg, Isobel Stewart, Scott T. Weiss, Augusto A. Litonjua, Jessica A. Lasky-Su

Lung function is known to decline with increasing age; however, the underlying mechanisms have yet to be fully elucidated. The aim of this study is to identify and validate metabolites associated with lung function level in adulthood utilizing two independent cohorts: the European Prospective Investigation into Cancer - Norfolk (EPIC-Norfolk) and the Normative Aging Study (NAS). We included 10,460 and 396 participants from EPIC and NAS respectively, for whom we have global metabolomic profiling with concurrent measures of lung function, including forced expiratory volume in one second (FEV1) and FEV1/forced vital capacity (FEV1/FVC). We employed multivariable regression models to identify metabolites associated with pulmonary function level, accounting for multiple testing. Nine FEV1 associated metabolites replicated in both cohorts. These included several omega-3 fatty acids: Docosahexaenoate 22:6n3 (EPIC: β = 2.85; p = 5.37x10-10, NAS: β = 0.115; p = 0.017); Docosapentaenoate 22:5n3 (EPIC: β = 2.06; p = 4.84x10-6, NAS: β = 0.107; p = 0.026); and, Eicosapentaenoate 20:5n3 (EPIC: β = 1.82; p = 5.80x10-5, NAS: β = 0.090; p = 0.038). These metabolites may influence pulmonary health through their anti-inflammatory effects. Two FEV1/FVC associated metabolites, both amino acids, replicated between the cohorts: cysteine-glutathione disulfide (EPIC: β = -0.0077, p = 1.07x10-12; NAS: β = -0.012, p = 0.017) and threonine (EPIC: β = -0.00283, p = 0.00855; NAS: β = -0.030, p = 0.012). These validated metabolites provide novel insights into the mechanisms of respiratory health.

P-10 Senescent cell metabolome reveals a novel lipid drivers and biomarkers in vitro and in vivo

PRESENTING AUTHOR: Arvind Ramanathan, Buck Institute, United States

CO-AUTHORS: Rishi Sharma, Chris Wiley, Judith Campisi

Cellular senescence is a multifaceted response to cellular stress or damage that results in both a permanent mitotic arrest and secretion of a number of factors with potent biological activities1-4. This senescence-associated secretory phenotype, or SASP, has largely been studied in the context of secreted proteins, many of which have been shown to have key roles in several processes including development, aging, wound healing, arthrosclerosis, cancer progression and fibrosis2,5-9. By comparison, secretion of lipids and other molecules has been understudied in the context of senescence. Here we show that senescent cells activate biosynthesis of eicosanoids – signaling lipids with potent biological effects, and this activity both promotes the inflammatory part of the SASP and reinforces mitotic arrest by a Ras-P53 axis. An finally these lipids serve as biomarkers of senolysis in vitro and in vivo.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

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BIOMEDICAL

P-11 The Aging Lung

PRESENTING AUTHOR: *Charmion Cruickshank-Quinn, Agilent Technologies, United States*

CO-AUTHORS: *Roger Powell, Irina Petrache, Nichole Reisdorph*

Lung function declines with age and increases susceptibility to a variety of lung ailments including chronic obstruction and respiratory infections in older adults. This decline has a greater effect on patients with COPD and asthma compared to healthy aging adults. To understand the effects of healthy aging on the lung environment, bronchoalveolar lavage (BAL) fluid of female C57BL/6 mice aged 3 months (young) and 12 months (old) (n=6/group) was collected from littermates housed under the same conditions. Samples underwent LC/MS untargeted metabolomics (Agilent 6220 ESI-TOF and 6560 IMMS QTOF). Spectral peaks were extracted, aligned based on accurate mass and retention time (Profinder) and missing values imputed (InfernoRDN). Compound names were assigned using an in-house library built from authentic standards using accurate mass, retention time and MS/MS or searched using exact mass and isotope ratios (MPP). T-tests were performed (Benjamini Hochberg ≤ 0.05) with fold change ≥ 1.25 (MPP). Ceramides such as Cer(d40:1) and lipid mediators such as HDHA are depleted with age. Pathway enrichment revealed non-small cell lung cancer as a perturbed pathway, where its entities DG(34:2), DG(36:3) and retinoic acid were decreased in older mice. Results suggest an age-lipid metabolism association and may signify cell membrane breakdown due to the loss of elasticity in the lungs. This study is important for understanding the effects of aging on the lung to distinguish between the normal aging process versus lung decline due to disease. Supplementation to restore the depleted compounds may help to alleviate some of the effects of aging.

P-12 Famine exposure during prenatal development has life long effect on lipid metabolism, which may in turn effect cognition

PRESENTING AUTHOR: *Stuart Snowden, University of Cambridge, United Kingdom*

CO-AUTHORS: *Susanne de Rooji, Aniko Korosi, Albert Koulman*

The concept that early life exposures can affect later life health is well established, and whilst differences in the lipid metabolism around the time of exposure are widely reported little work has been performed to see how lipid metabolism in later life is affected. In this study we determined if exposure to famine in utero, had a measurable effect on lipid metabolism in healthy individuals aged 60, and if these differences on the wider lipid metabolism were associated with cognitive health. Direct infusion mass spectrometry was performed on 777 human plasma samples, 448 from famine exposed individuals and 329 controls, matched for BMI etc. Random forest approaches were used to identify markers of famine exposure, as well as determine if lipid data could be used to predict cognitive performance and leptin levels. Generated models were able to predict famine exposure with a modest accuracy (64.1%) with these predictions predominantly being driven by 5 lipids, 2 cholesteryl esters and 3 phosphatidylethanolamines. Significant correlations between predicted and actual values of brain age (r = 0.529, p = 0.003) and leptin (r = 0.598, p = 3.1×10-14) were observed in models calculated using the whole of the lipid profile data, with lysophosphatidylcholines playing a crucial role in models of both brain age and leptin. In utero exposure to famine has a lasting effect on lipid metabolism with leptin potentially involved in mediating the observed metabolic reprogramming. The results also suggest a link between leptin and famine related cognitive decline via lysophosphatidylcholine metabolism.

P-13 Tandem mass spectrometry analysis of urinary methylmalonic acid as marker of metabolic vitamin B12 deficiency in older adults

PRESENTING AUTHOR: *Michel Boutin, Université de Sherbrooke, Canada*

CO-AUTHORS: *Tristan Martineau, Audrey Perreault, Pierrette Gaudreau, Nancy Presse, Christiane Auray-Blais*

Vitamin B12 deficiency can lead to potentially irreversible neurological symptoms (e.g. memory deficits, gait ataxia). Up to 40% of older adults show metabolism abnormalities due to B12 deficiency. However, most present with normal levels of serum B12 so that this condition often remains under-recognized. Metabolic B12 deficiency causes an elevation of serum methylmalonic acid (MMA), an expensive test rarely available in clinical settings. Urine MMA also increases in cases of B12 deficiency, but it is unclear whether it correlates with serum MMA and can be used for diagnostic purposes. This study examined the correlation between serum and urine MMA in 35 older adults (>70 years) from the NuAge cohort with serum MMA levels varying from 165 to 15285 nmol/L. A reliable UPLC-MS/MS method for the multiplex urine analysis of MMA and creatinine was developed and validated. Briefly, 30 µL of urine was mixed with 60 µL of water containing MMA-D3 and creatinine-D3 as internal standards. A 2-minute reverse phase chromatographic method allowed the separation of MMA from succinic acid, a major isomeric interference. The Acquity I-Class UPLC system (Waters Inc.) was used. The absolute quantitation of MMA and creatinine was achieved by tandem mass spectrometry (Xevo TQ-S Micro, Waters) using the multiple reaction monitoring mode. Our results show a significant correlation between urinary MMA/creatinine ratios and MMA serum levels (Spearman r=0.59). Urine MMA measured by this UPLC-MS/MS method is promising for diagnosing B12 deficiency. This method could also be applicable as a 2nd tier-test for MMA newborn urine screening.
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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.

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BIOMEDICAL

P-14

Systemic and central nervous system metabolic alterations in Alzheimer's disease

PRESENTING AUTHOR: Julijana Ivanisevic, University of Lausanne, Switzerland

CO-AUTHORS: Vera van der Velden, Tony Teav, Héctor Gallart-Ayala, Florence Mehl, Ioana Konz, Christopher Clark, Aikaterini Oikonomidi, Gwendoline Peyratout, Hugues Henry, Mauro Delorenzi, Julijana Ivanisevic and Julius Popp

Metabolic alterations play an important role in Alzheimer's disease (AD) on both the systemic and central nervous system (CNS) level. To study their extent and significance in AD, quantitative metabolomics was applied to samples from clinically well-characterized AD patients. The association of the observed metabolic alterations with core pathological processes of AD was explored to understand their relation with amyloid pathology and tau-related neurodegeneration. Metabolic profiling, i.e. untargeted metabolomics and targeted quantification, was performed on paired plasma and CSF samples from clinical and biomarker-confirmed AD patients (n=40) and cognitively healthy controls without cerebral AD pathology (n=34). Targeted quantification focused on identified deregulated pathways, such as the TCA cycle and its anaplerotic pathways, as well as the neuroactive tryptophan pathway. Concentrations of several TCA cycle and beta-oxidation intermediates were higher in plasma of AD patients, whilst amino acid concentrations were significantly lower. Similar alterations were observed in CSF, which were strongly correlated with blood-brain barrier permeability. Alterations of several amino acids in CSF were associated with CSF Amyloidβ1-42. The tryptophan catabolites kynurenine acid and quinolinic acid showed significantly higher concentrations in CSF of AD patients, which, together with other tryptophan pathway intermediates, were correlated with either CSF Amyloidβ1-42, or tau and phosphorylated Tau-181. These results revealed AD-associated systemic dysregulation of nutrient sensing and oxidation and CNS-specific alterations in the neuroactive tryptophan pathway. The specific association of amino acids and tryptophan catabolites with AD CSF biomarkers suggests a close relationship with core AD pathology.

P-15

Metabolomics for the discovery of new therapeutic approach and personalized medicine: the case of exudative Age-related Macular Degeneration

PRESENTING AUTHOR: Pascal de Tullio, University of Liège, CIRM, Metabolomics group, Belgium

CO-AUTHORS: Vincent Lambert, Matthieu Schoumacher, Julie Lecomte, Deniz Arslan, Justine Leenders, Bernadette Govaerts, Jean-Marie Rakic, Agnès Noël

Exudative Age-related Macular Degeneration, which is characterized by a choroidal neovascularization (CNV), is the leading cause of blindness among the elderly population in developed countries. Treatment is based on intra-vitreal injection of anti-VEGF. Nevertheless, the comprehensive understanding of the pathogenesis and the evolution of this multi-factorial disease remain incomplete. Moreover, due to the long-term disease chronicity and resistance to treatment, the continuous follow-up of patients, the personalization of treatment and the discovery of new therapeutic approaches are mandatory. Because metabolomics provides a unique and direct vision to pathologies and/or treatment administration, this approach seems particularly adapted to study CNV occurrence and evolution, and to get novel and innovative insights into AMD. We applied a NMR-based metabolomics approach on sera coming from both clinical (AMD patients and controls) and pre-clinical model (a murine model that mimics CNV development). In the human cohort but also in the mice model, lactate and lipoproteins profile emerge as the main key metabolites and could be correlated to the AMD active phase and CNV development. Pharmacological normalization of lactate levels in the mice model by blocking pyruvate dehydrogenase kinase (PDK) or anti-VEGF treatments inhibits CNV formation and modified lipoproteins profiles. Mechanistically, we explore the role of lactate and we studied the modification of lipoproteins profiles according to CNV development. Altogether, we demonstrate that metabolomics is a suitable tool to deep insight into AMD and to identify some metabolites as functional, traceable and targetable molecules that open new perspectives for optimizing and personalizing treatment and patient follow-up.

P-16

Effect of calorie restriction on metabolic phenotypes of intestinal tissues in an aging model

PRESENTING AUTHOR: So Young Lim, Chonnam National University, South Korea

CO-AUTHORS: Young-Shick Hong

Aging accompanies the degeneration of intestinal metabolism and this intestinal dysfunction causes adverse effects to the host metabolism. Calorie restriction (CR) is an effective intervention to delay aging. However, the modification of intestinal metabolites by CR in aged model has been poorly understood. Therefore, we investigated the metabolic effect of 40% CR in various intestinal tissues and feces in an aged rat model, through 1H NMR-based metabolomics approach. The levels of fecal acetate in CR mice were significantly increased compared to control mice, indicating the alteration of the gut microbiota composition under CR condition. Moreover, the metabolic perturbation associated with nucleotide metabolism, osmoregulation, oxidative stress and bile acid metabolism were observed in the intestinal tissues of CR mice. Taken together, these metabolic features demonstrate that CR contributes to improvement of intestinal dysfunction caused by aging.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

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BIOMEDICAL

P-17 A Single Tissue Section Analysis Using Desi-msi and Laser Capture Microdissection for a Multimodal Cancer Research

PRESENTING AUTHOR: Emine Kazanc, Imperial College of London, United Kingdom

Using clinical specimens for multiple approaches including desorption electrospray ionisation (DESI-MSI) with transcriptomic can be challenging. Downstream analysis needs more adjacent sections. Therefore, a multimodal approach in same slide would allow to co-register different types of information providing a comprehensive knowledge about molecular characterising of diseases in particularly cancer. The envisioned combination analysis raises special requirements including short DESI-MSI run time to prevent RNA degradation during analysis in room temperature. The isolated RNA must have sufficient quality to carry out qPCR, RNA seq for transcriptomics. Clinical samples were obtained from Imperial College Tissue Bank. Tissues from patient with ovarian cancer were cryosectioned at 10 µm. The DESI-MSI spectrum was collected from sections and same sections were stained with haematoxylin and eosin in RNase free conditions. Next, the regions of interest in the same slide were microdissected by Laser Capture Microdissection (Leica 7000) and RNA was isolated. RNA quality control was done by the Agilent 2100 Bioanalyzer for qPCR and Sequencing. Preliminary results showed that the RNA amount is slightly less in DESI-MSI analysed slides than non-analysed slides. Having less RNA from the DESI-MSI analysed of samples can be attributed to different reasons including analysis at room temperature causing RNA degradation. The RNA degradation of each sample was evaluated measuring the RNA Integrity Number (RIN). The results of Agilent showed that the RNA quality of samples was sufficiently good to carry out downstream analysis to identify specific genes expression, which are related with the identified metabolic profiling by DESI-MSI.

P-18 Adipocyte-induced metabolic changes in HER2-positive cancer cells: understanding breast cancer resistance to targeted therapies

PRESENTING AUTHOR: Manhal Mili, Institute of Analytical Sciences, France

Targeted therapies have revolutionized the management of HER2-positive breast cancer, a particularly invasive form of cancer that responds poorly to conventional chemotherapy. However, resistance to treatment occurs in 25-60% of patients, presenting a new therapeutic challenge. Adipocytes were previously shown to act on HER2+ cells to decrease their sensitivity to targeted therapy (monoclonal antibody trastuzumab) in co-culture. Addition of a lipolysis stimulator (isoprenaline, a beta-adrenoreceptor agonist) to the system led to further decrease of HER2+ cancer cells response to trastuzumab while conversely, addition of a lipolysis inhibitor (beta-blocker propranolol) rescued the response to therapy. In order to understand the underlying mechanisms of adipocyte-modulated cancer cells resistance to trastuzumab, we present here a detailed pharmaco-metabolomic investigation of adipocyte and HER2+ cancer cell co-cultures and associated controls, conducted with or without addition of propranolol and isoprenaline. 1H 800 MHz NMR profiles were recorded to quantify metabolites present in the co-cultures supernatants and to assess the respective endometabolomes of adipocytes and HER2+ cancer cells. Quantitative analysis of HER2+ cell fingerprints (41 quantified metabolites) demonstrates substantial variations of metabolite concentrations in the presence of propranolol or isoprenaline, notably succinate and glycerol. We show that propranolol and isoprenaline, in addition to their impact on lipolysis, induced changes in adipocytes in the concentrations of UDP-glucose, 1-methylnicotinamide and several amino-acids. These results hint at a broad impact of adipocytes on HER2+ cell metabolism. Overall, our metabolomics investigation provides new insights into the mechanisms by which pharmacological modulation of lipolysis via beta-adrenoreceptors impact on HER2+ cancer cell metabolism.

P-19 NMR-based metabolomics in real-time monitoring of treatment induced toxicity in head and neck cancer and influence of individual genetic profile

PRESENTING AUTHOR: Łukasz Boguszewicz, Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Poland

CO-AUTHORS: Agata Biełeń, Mateusz Ciszek, Jolanta Mrochem-Kwarciak, Andrzej Wygoda, Tomasz Rutkowski, Dorota Butkiewicz, Małgorzata Krześniak, Agnieszka Gdowicz-Kłosok, Anna Kotylak, Agnieszka Skorupa, Krzysztof Składowski, Maria Sokół

Introduction: The standard treatment for head and neck cancer (HNSCC) is radio-/chemoradiotherapy (RT/CHRT). However, it is associated with significant temporary or permanent toxic side effects in normal tissue and/or involved regions (acute radiation sequelae, ARS). In this study we investigated the real-time dynamic changes in serum metabolome during RT/CHRT in HNSCC patients to identify biomarkers of early ARS and to find their association with selected genetic variants affecting anticancer treatment response. Methods: The studied group consisted of 220 patients (22-80 years) treated with radical intent for hypopharynx, larynx, nasopharynx and oropharynx cancers. Blood serum samples were collected weekly from the day before the treatment till the RT/CHRT completion. 1H NMR spectra were acquired on a Bruker 400.13MHz spectrometer (NOESY, CPMG, diffusion edited and J-resolved sequences). Genetic polymorphisms were detected by PCR-RFLP or TaqMan probes. The data were analyzed using SIMCA (principal component analysis, partial least squares - discriminant analysis) and STATISTICA software. Results: We identified a group of outlying patients with a massive increase of signals arising from the ketone bodies (3-hydroxybutyrate, acetone, acetoacetate). Such increase correlated with the episodes of severe functional and morphological ARS. Furthermore, the NBS1 and GSTM1 polymorphisms were significantly associated with different disturbances in the serum metabolome and ARS severity (via the impact on energy metabolism and inflammation). Conclusions: Real-time molecular monitoring during RT/CHRT could be beneficial for early detection of patients with poor treatment tolerance. This work was supported by the National Science Centre (NCN), Poland, grants no. 2016/23/B/NZ5/03470 and 2015/17/B/NZ5/01387.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

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P-20 Combined metabolite and gene expression profiling predicts biochemical recurrence in prostate cancer radiotherapy patients

PRESENTING AUTHOR: Therese Stork Høiem, NTNU, Norway

CO-AUTHORS: Ailin F. Hansen, Therese S. Høiem*, Kirsten M. Selnæs, Anna M. Bofin, Helena Bertilsson, Øystein Størkersen, Tone F. Bathen, Guro F. Giskeødegaard, Morten B. Rye, May-Britt Tessem

Biomarkers for prostate cancer (PCa) recurrence are highly needed for better management and follow-up of radiotherapy patients. Up-regulation of TOP2A and EZH2 have previously been connected to a more aggressive disease in radical prostatectomy (RP) patients. Further, low tissue levels of the metabolites citrate and spermine have been associated with biochemical recurrence (BCR, PSA≥0.2 ng/ml) in RP patients. The main aim of the present study was to investigate the potential of gene expression and MR tissue metabolites as biomarkers for BCR in transrectal ultrasound-guided (TRUS) biopsies of PCa radiotherapy patients prior to treatment (n=172 samples). TOP2A and EZH2 expression were assessed using immunohistochemistry, and high-resolution magic angle spinning MR spectroscopy was performed to measure metabolites in the same TRUS biopsy. In cancer patient samples without hormone treatment, concurrent up-regulation of TOP2A and EZH2 were identified as predictors of BCR among PCa radiotherapy patients (n=31, p=0.0079). Lower levels of citrate (p=0.0037) and polyamines (p=0.0057) prove the same. TOP2A and EZH2 in combination with significantly lower levels of either citrate or polyamines in cancer samples was confirmed as potential biomarkers for BCR among radiotherapy patients in TRUS biopsies collected prior to treatment (n=6, p=0.00027, p<0.0001 respectively). In conclusion, combination of TOP2A and EZH2, MR metabolites citrate and polyamines are suggested as biomarkers for BCR in PCa radiotherapy patients not receiving neoadjuvant hormonal treatment measured in TRUS biopsies prior to treatment; however, this needs validation in a larger cohort. This study offers a translational potential detecting metabolites using in vivo MR spectroscopic imaging.

P-21 Urinary GC-MS untargeted metabolomics for prostate cancer diagnosis. Preliminary results

PRESENTING AUTHOR: Eleonora Amante, Università degli Studi di Torino, Italy

CO-AUTHORS: Alessandra Biancolillo, Rasmus Bro, Francesco Porpiglia, Alberto Salomone, Marco Vincenti

Prostate carcinoma is the principal cause of cancer-related death in men. The prostate specific antigen (PSA) dosage is, at the present, the unique clinical test available to screen for this pathology. PSA is highly sensitive but not enough specific for malignancy, providing a significant amount of misleading results. Thus, new biomarkers which could improve the diagnostic power of prostate screenings are needed. The present work is a preliminary study aimed to discover new urinary biomarkers suitable for this purpose. Ninety subjects, divided into controls and prostate carcinoma-affected, were recruited. Two aliquots of each sample were treated as follows: proteins were precipitated, two subsequent extractions (at acid and basic conditions) were performed for each aliquot and the dried extracts were derivatized using trifluoroacetic anhydride (aliquot A) and trimethylsilyl derivatizing mixture (aliquot B). The full-SCAN GC-MS spectra (two for each sample) were then processed with the following chemometric approach: (i) the alignment was performed by double warping algorithm; (ii) The spectral deconvolution was carried out using the PARADIS software, based on the PARAFAC2 algorithm; (iii) The semiquantitative report provided by the software was then subjected to two different and independent variable selection procedures: (a) Variable Importance Projection and (b) Covariance Selection algorithm; (iv) The reduced datasets were used to build two classification models, which performances were compared. The validation of the models was performed using a repeated double cross validation approach, and the obtained preliminary results are promising, scoring near to 90% for both specificity and sensitivity.

P-22 Novel metabolomic predictors of incident colorectal cancer in men and women

PRESENTING AUTHOR: Amit Joshi, Massachusetts General Hospital and Harvard Medical School, United States

CO-AUTHORS: Amit D. Joshi, Brendan J. Guercio, Oana A. Zeleznik, Mingyang Song, Fred K. Tabung, A. Heather Eliassen, Kana Wu, Charles S. Fuchs, Edward Giovannucci, Jeffrey A. Meyerhardt, Andrew T. Chan

Background: Metabolomic profiles reflect the combined influence of genetic and lifestyle factors in the development of colorectal cancer (CRC). To date, few prospective studies have conducted metabolome-wide association analyses of pre-diagnostic plasma in CRC risk. Methods: We conducted a nested case-control study among 32,786 women (Nurses' Health Study [NHS]) and 18,159 men (Health Professionals Follow-up Study [HPFS]) who provided blood ("60% fasting) between 1989-95. Over a 17-year follow-up period, we documented 665 (409 in NHS, 256 in HPFS) incident CRC cases which were matched 1:1 to 665 controls based on cohort, age, race, time of collection, and fasting status. We conducted metabolomic profiling using liquid chromatography-mass spectrometry to identify 530 known plasma metabolites. Weighted correlation network analysis (WGCNA) was done to obtain modules of interconnected molecules with high topological overlap. Logistic regression was used for association analyses, and multiple comparisons correction was performed using α-threshold P<8.5x10-4. Results: We observed significant associations with CRC risk for 5 metabolites, including C58:7-TAG (OR=0.81,P=6.6x10-4) in all participants, myristoleic acid (OR=1.32,P=4.3x10-4) in women, and N2,N2-dimethylguanosine (OR=1.61,P=4.8x10-4) in men. Associations were stronger when restricted to fasting samples. Among WGCNA-derived modules, association differed according to sex, with nucleic acid module associated with CRC in men (P=0.010), and carnitine module associated in all participants (P=0.013). Conclusions: We identified prediagnostic metabolites associated with CRC in 3 groups, acylglcyerols, purines, and ω-5-fatty acids, with distinct profiles in men compared with women. These results provide insight into the etiopathogenesis of CRC and have implications for risk prediction and novel prevention strategies.
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P-23 Evaluation of urinary volatile metabolites as potential biomarkers for prostate cancer diagnosis

PRESENTING AUTHOR: Ana Rita Lima, UCIBIO-Requimte, Faculty of Pharmacy of the University of Porto (FFUP), Portugal

CO-AUTHORS: Ana Rita Lima, Joana Pinto, Ana Isabel Azevedo, Carmen Jerónimo, Rui Henrique, Maria de Lourdes Bastos, Márcia Carvalho, Paula Guedes de Pinho

Prostate cancer (PCa) is the second most common malignancy in men. Prostate specific antigen (PSA) is the most frequently used biomarker for PCa screening but, due to its recognized limitations, nowadays, U.S. Preventive Services Task Force recommends against PSA screening. The analysis of volatile compounds emanating from biological samples is a major promising approach for finding new effective diagnostic markers for PCa. The purpose of this work was to study the urinary volatile metabolic profile of patients with PCa (n=40) and non-cancer controls (n=42) with the aim of identifying a potential urinary volatile pattern as a non-invasive strategy to detect PCa. A metabolomics approach based on headspace solid-phase microextraction gas chromatography–mass spectrometry was performed to investigate volatile organic compounds (VOCs) in general and, more specifically, volatile carbonyl compounds (VCCs) present in urine samples. Considering both approaches, a panel of 30 volatile compounds descriptive of PCa was defined, capable of discriminating PCa patients from controls. Furthermore, an external validation set (n=18 PCa and n=18 non-cancer controls) was used to calculate the sensitivity, specificity and accuracy of the defined panel. Our results revealed that this panel of 30-volatiles was able to perfectly predict PCa, with 100% sensitivity, specificity and accuracy. Overall, our results disclose a biomarker panel that has the potential to be used in clinic for PCa diagnosis. A.R.L thanks FCT, Portugal, for her PhD grant (SFRH/BD/123012/2016). This work was financed by national funds from FCT/MEC (UID/Multi/04378/2013) and co-financed by the ERDF under the PT2020 Partnership Agreement (POCI/01/0145/FEDER/007728).

P-24 Associations between metabolites and pancreatic adenocarcinoma risk in a large prospective study

PRESENTING AUTHOR: Rachael Stolzenberg-Solomon, DCEG, NCI, NIH, United States

CO-AUTHORS: Andriy Derkach, Steve Moore, Stephanie Weinstein, Demetrius Albanes, Joshua Sampson

Background: Metabolomics profiles may offer improved insights into etiology and the system of factors involved in the process of pancreatic adenocarcinoma (PDAC) tumorigenesis. Methods: We conducted an untargeted analysis of 554 known metabolites measured in pre-diagnostic serum (up to 24 years) to determine their association with incident PDAC in a nested-case control study of male smokers (373 matched case-control sets) with replication in an independent nested-case control study in that included women and non-smokers (107 matched sets). Controls were matched to cases by age, sex, race, date of blood draw and follow-up time. We used conditional logistic regression to calculate odds ratios (OR) and 95% confidence intervals (CI) for a 1 standard deviation increase in log-metabolite level separately in each cohort and combined the two ORs using a fixed effects meta-analysis. Results: Thirty-one metabolites were significantly associated with PDAC at an FDR < 0.05 with 12 metabolites below the Bonferroni-corrected threshold (P-value < 9.04 x 10-5). Similar associations were observed in both cohorts. The dipeptides glycylvaline, aspartylphenylalanine, pyroglutamylglycine, phenylalanylphenylalanine, phenylalanylleucine, and tryptophylglutamate and amino acids aspartate and glutamate were positively while the dipeptides tyrosylglutamine and α-glutamylyrosine, fibrinogen cleavage peptide DSGEGDFXAEGGGVR, and glutathione related amino acid cysteine-glutathione disulfide were inversely associated with PDAC after Bonferroni correction. Five top metabolites demonstrated significant time varying associations (P-value < 0.023) with associations becoming attenuated 10-15 years after participants' blood collection. Conclusion: Our results demonstrate pre-diagnostic metabolites related to subclinical disease, glutathione metabolism, and adiposity/insulin resistance are associated with PDAC.

P-25 Exploratory metabolomics of urine and plasma to identify novel pharmacodynamic biomarkers in a phase I clinical trial of AZD3965

PRESENTING AUTHOR: Alexandros Siskos, Imperial College London, United Kingdom

CO-AUTHORS: CH Lau, S. Halford, P. Jones, S. Hirschberg, G. Veal, G. Payne, M. Chenard-Poirier, U. Banerji, S. Wedge, E. Aboagye, R. Plummer, Hector Keun

A key metabolic alteration in tumour cells is increased dependency on glycolysis, resulting in the production of lactate which is transported out of cells by monocarboxylate transporters (MCT1 & MCT4) which are therefore a therapeutic target in cancer. Current literature suggests that inhibition of MCT1 in preclinical models can constrain cancer cell growth in tumours with low MCT4 expression. To date the systemic pharmacodynamic effects of the small-molecule non-competitive inhibitor of MCT1, AZD3965, the agent of study in this first-in-class (FIC) trial CRUKD12/004, have not been fully characterised. Preclinical metabolomics studies conducted at Imperial College London indicated that AZD3965 exposure caused increases in lactate, ketone bodies (also MCT1 substrates) and citrate in blood plasma and urine independently of tumour burden and tumour expression of MCT1, and also caused decreases in fatty acids in blood plasma. We used NMR spectroscopy of urine and plasma samples from 34 patients from the trial to specifically monitor lactate and other ketone bodies and in addition a metabolomics screen using a well-validated LC-MS/MS protocol (Biocrates AbsoluteIDQ p180 kit) on plasma. Metabolomics profile of plasma and urine appears to reflect response of AZD3965 treatment, and especially total urinary excretion of lactate and ketone bodies offers proof of target engagement. This effect is not mirrored in plasma suggesting that this may be primarily a renal effect. Observed systemic metabolic effects of AZD3965 exposure appear to lessen with repeated dosing, suggesting a rapid adaptive response. Metabolomics profile can offer insides in understanding the mechanism of drug toxicity.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

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P-26 Preoperative Metabolomic Signature of Prostate Cancer Recurrence.

PRESENTING AUTHOR: David Gaul, Georgia Institute of Technology, United States

CO-AUTHORS: Chaevien S. Clendinen, Rebecca S. Arnold, John A. Petros, Arthur S. Edison, Facundo M. Fernández

Up to 50% of prostate cancer surgical patients will suffer from biochemical recurrence manifested by detectable serum prostate specific antigen levels even after prostate removal. Relatively limited pre-operative information has not yielded adequate prognosis to guide a patient's treatment decision. More clinical data is needed to improve prognosis. New biomarkers can arise from metabolome analysis of patient serum to aid physicians and patients in developing a treatment plan. We applied a multiplatform (NMR + LC-MS) metabolomics approach to the study of preoperative metabolic alterations associated with prostate cancer recurrence. Correlation analysis on the serum metabolite abundances from prostate cancer patients (n = 40 remission vs n = 40 recurrence) showed significant alterations in several pathways, including amino acid metabolism, purine and pyrimidine synthesis, tricarboxylic acid cycle, tryptophan catabolism, glucose, and lactate. In addition, higher lipid abundances were observed in the serum from recurrent patients for several classes that included triglycerides, lysophosphatidylcholines, phosphatidylethanolamines, phosphatidylinositol, diglycerides, acyl carnitines, and ceramides. Machine learning approaches led to the selection of a 20-metabolite panel from a single preoperative blood sample that enabled prediction of recurrence with 92.6% accuracy, 94.4% sensitivity, and 91.9% specificity under cross-validation conditions.

P-27 A Metabolomics-based Adaptive Strategy for Monitoring and Delivering Systemic Therapy

PRESENTING AUTHOR: Jodi Rattner, University of Calgary, Canada

CO-AUTHORS: Chris O'Callaghan, Dongsheng Tu, Patricia A. Tang, Lillian L. Siu, Jeremy Shapiro, Karen Kopciuk, Hans J. Vogel, Oliver F. Bathe

Background. Chemotherapy options for treating colorectal cancer (CRC) have expanded in recent years. Treatment benefit is assessed in a costly and untimely manner, typically by serial CT scans beginning 2 – 3 months after starting drug. Our aim was to develop a blood-based biomarker that would identify patients who are not responding to chemotherapy, soon after chemotherapy is initiated. Methods. Samples and linked clinical data of metastatic colorectal cancer patients were obtained from a large clinical trial (NCIC-CTG CO.20)Response to chemotherapy was determined by RECIST 1.1 criteria. Serial plasma metabolomic profiles from a discovery set of patients(n=68), treated with cetuximab or cetuxinab+brivanib, and disease-free controls(n=48) were analysed using gas chromatography-mass spectrometry (GC-MS). A response model for CRC was derived using orthogonal partial least squares-discriminant analysis (O-PLS-DA) based on treatment-related changes in metabolites. Metabolomic models suitable for distinguishing response categories and progression of disease were generated. Results. Using GC-MS, 386 compounds were detected. By as early as 4 weeks after chemotherapy was initiated, treatment-related changes that discriminated measurable response, stable disease and progression could be detected. The model that signaled disease progression (which marks treatment futility) was robust (R2Y=0.822; Q2Y=0.605; P-Value<0.0001). This biomarker consisted of 25 metabolites, including important intermediates involved in nucleotide synthesis and energy metabolism. Conclusions. Treatment-related changes in circulating metabolites appear shortly after initiating chemotherapy. The pattern of changes varies with the type of treatment response. Progressive disease has a particularly distinct set of changes. External validation will be required to further assess these biomarkers.

P-28

Untargeted metabolomics of archived dried blood spots reveals evidence of maternal and neonatal nutrition as risk factors for childhood leukemia

PRESENTING AUTHOR: Lauren Petrick, Icahn School of Medicine at Mt. Sinai, United States

CO-AUTHORS: Courtney Schiffman, William M.B. Edmands, Yukiko Yano, Kelsi Perttula, Todd Whitehead, Catherine Metayer, Craig E. Wheelock, Manish Arora, Hasmik Grigoryan, Henrik Carlsson, Sandrine Dudoit, Stephen M. Rappaport

Early-life exposures are believed to play an important etiologic role in the development of pediatric acute lymphoblastic leukemia (ALL). Yet direct analysis of exposures have not been undertaken to date, primarily due to technological barriers. Archived neonatal blood spots (NBS) collected within the first days of life offer a means to investigate small molecules that reflect early-life exposures and biological response that pre-date the onset of clinical disease. We obtained NBS for 334 ALL cases and 324 healthy matched controls as part of the California Childhood Leukemia Study. Untargeted metabolomics was performed on the extracts of NBS punches (4.7-mm, ~ 8 µL of blood), with an Agilent 1290 UHPLC system connected to a 6550 QTOF HRMS (Santa Clara, USA) in ESI (-) mode. Subjects were stratified by early (1-5 y) and late (6-14 y) diagnosis, and an ensemble of feature-selection methods used to pinpoint metabolites predictive of case status. Covariates representing suspected risk factors for ALL were also evaluated. Mutually-exclusive sets of lipids and fatty acids were associated with ALL phenotypes, including 9 and 19 metabolites in the early- and late-diagnosis groups, respectively. In the late-diagnosis group, a prominent cluster of metabolites contained molecules with 18:2 fatty-acid chains, suggesting that newborn exposure to the essential nutrient, linoleic acid, increased ALL risk. Interestingly, abundances of these 18:2 lipids were greater in infants who were fed formula rather than breast milk (colostrum) and increased with the mother's pre-pregnancy body mass index, suggesting possible etiologic roles of newborn nutrition.
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P-29

Relevance of (R,R')-4'-methoxy-1-naphthylfenoterol for treatment against metastatic colorectal cancer

PRESENTING AUTHOR: Danuta Dudzik, Medical University of Gdańsk, Poland

CO-AUTHORS: Danuta Dudzik1,2, Irving W. Wainer3, Wiktoria Struck-Lewicka1, Małgorzata Waszczuk-Jankowska1, Michał J. Markuszewski1, Michel Bernier4, Danuta Siluk1, 1 Department of Biopharmaceutics and Pharmacodynamics, Faculty of Pharmacy, Medical University of Gdańsk, Poland, 2 Center for Metabolomics and Bioanalysis (CEMBIO), Faculty of Pharmacy, San Pablo CEU University, Madrid, Spain, 3 PAZ Pharmaceuticals, Washington, DC, USA, 4 National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA

Metastatic colorectal cancer (CRC) is the third leading cause of cancer-related death worldwide. The clinical management is challenging due to CRC innate and/or acquired multidrug resistance to standard and targeted chemotherapies as well as resistance to immuno-oncology approaches. We studied the anticancer effects of 4'-methoxy-1-naphthylfenoterol (MNF) acting through the inhibition of G protein-coupled receptor GPR55 and activation of the β2-adrenergic receptor. We provide the results from untargeted metabolomics analysis of plasma and tumor tissues obtained from (R,R')-MNF-treated and control animals, designed to explore the biological mechanisms associated with the observed antitumor response and to identify potential biomarkers of these effects. Female BALB/c mice with a subcutaneous CT26 CRC tumor were divided into three experimental groups: (R,R')-MNF at 20mg/kg (n=9) or 30mg/kg (n=8), and a vehicle-treated (n=10). The changes in plasma and tumor metabolomic profiles associated with the MNF action were evaluated by liquid chromatography mass spectrometry (RP-HPLC-ESI-TOF-MS) analysis. Raw data acquired was pre-processed, filtered, and corrected for signal drift. A combination of univariate and multivariate statistical analyses was used to evaluate the drug effect on CRC. Metabolite annotation was accomplished by searching against several databases including HMDB, KEGG, Metlin, and LipidMaps. Among the most differentiated metabolites whose levels were significantly impacted by MNF were those belonging to the lipid metabolism pathway, including glycerolipids, glycerophospholipids, and sterol lipids. These results are consistent with our previous data reporting MNF activity in pancreatic cancer. The knowledge generated in this study has advanced our understanding of the anticancer molecular mechanisms of MNF.

P-30

The discovery of potential cancer biomarkers in human plasma using GC- and GCxGC-TOFMS

PRESENTING AUTHOR: Ralf Loescher, LECO European Application and Technology Center, Germany

CO-AUTHORS: David E. Alonso, Joe Binkley, Habtom Ressom, Cristina Di Poto

High mortality rates exist for individuals with hepatocellular carcinoma. There is a critical need for discovery of early stage HCC biomarkers to elicit rapid and effective treatments. GC-MS based metabolomics is an ideal approach for investigating cancer physiology for discovery of liver disease diagnostic markers. The objective of this research study was to implement an untargeted, multiplatform, analytical approach for identification of candidate HCC biomarkers in humans using comprehensive GC- and GCxGC-TOFMS. After sample preparation the dry samples were derivatized in two-steps: 1) Methoximation and 2) silylation. Derivatized samples and quality control standards were injected into the chromatograph and separation performed using two different polarity columns. Mass spectra were collected using a mass range of 50 to 510 and an acquisition rate of 10 spectra per second (200 sps for GCxGC). Data were processed using untargeted Peak Find and compounds were characterized through retention index filtering, similarity searches and formula determinations. Analyses of plasma samples resulted in composition maps displaying a wide variety of compounds including acids, diacids, amino acids, bases, fatty acids, a large assortment of simple sugars, and reduced/oxidized sugars. Transitioning from GC-TOFMS to high performance GCxGC-TOFMS resulted in a greater than 2-fold increase in characterized compounds. Statistical processing of the data led to the identification of potential candidate markers for HCC disease including organic acids, amino acids and reduced sugars.

P-31

Volatile organic compounds as biomarkers of prognosis in palliative lung cancer patients

PRESENTING AUTHOR: Elinor Chapman, Palliative Care Institute Liverpool, University of Liverpool, United Kingdom

CO-AUTHORS: David Hughes, John Ellershaw, Mark Boyd, Chris Probert, Seamus Coyle

Diagnosing dying and predicting prognosis for palliative patients is an ongoing problem for physicians as there are few good biomarkers (Reid, VL et al., PLoS One, 2017). Having more certainty about prognosis is crucial for patients, their families and clinicians to provide the best care possible. We hypothesise there is a metabolic process to dying that could yield quantifiable biomarkers. A feasibility study showed that volatile organic compounds (VOCs) in urine changed in the last days and weeks of life in a small mixed cancer group (Coyle, S. et al., BMJ Open, 2016). In this pilot study: 424 urine samples were collected from 162 patients with advanced lung cancer from six sites across Merseyside. 63 patients provided a sample in the last month (28 days) of life and 29 patients in the last week of life. Urinary VOCs were examined by gas chromatography-mass spectrometry (GC-MS). Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression was used to analyse data and create models. A model predicting whether an individual would die within three days based on only two VOCs, generated an AUC = 0.80 (0.68-0.93), was 93% specific and 68% sensitive. Other models predicting between 4-10 days of life or 11-17 days of life remaining were generated. Urine analysis could be used to predict the dying process and lead to the identification of prognostic biomarkers. Future work will focus on optimisation of urinary VOC analysis, refinement of models and verifying in a validation cohort of patients with lung and other cancers.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

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P-32

Metabolic alterations in patients with cancer: searching for metabolomic biomarkers of breast cancer

**PRESENTING AUTHOR:** Matea Nikolac Perkovic, CEMBIO, University San Pablo CEU (Madrid, Spain); Ruđer Bošković Institute (Zagreb, Croatia), Spain

**CO- AUTHORS:** David Rojo Blanco, Marija Kirzic, Natalija Dedic Pavletic, Kamelija Zarkovic, Damir Vrbanec, Biserka Orehovec, Coral Barbas, Neven Zarkovic

Breast cancer (BC) is a heterogeneous disease and one of the major causes of cancer death in women. One of the main hallmarks of cancer is the ability of cancer cells to alter their metabolic phenotype, which allows them to survive and proliferate against all odds. Therefore, the aim of this study was to apply LC-MS based untargeted metabolomics approach, as previously described [1], in order to identify new metabolomic biomarkers associated with BC pathology. Study included plasma samples from BC patients prior to any treatment (N=41) and matching controls (N=30). Fifty- seven chemical compounds were found to be significantly altered in BC patients. The resulting list of statistically significant accurate masses was annotated using the CEU Mass Mediator search tool (http://ceumass.eps.uspceu.es/mediator/), and the biological role of suggested compounds was additionally evaluated to exclude the less probable identification matches. Our results indicate a significant increase in the expression of different fatty acyls, including several straight chain, branched and unsaturated fatty acids, docosanoids, eicosanoids, octadecanoids, fatty aldehydes and amides. Increased levels of certain monoacylglycerols and different glycerophospholipids were also found to be characteristic for BC subjects. We also detected alteration of amino acid and bilirubin metabolism in BC patients and differential expression of C19 and C20 steroids. These findings suggest a key role of lipid classes and molecular species in BC growth and development and possibly lead us a step closer to new metabolomic biomarkers in BC.

P-33

Investigating the drug responsiveness on the metabolic pathways in PDAC-PDX models

**PRESENTING AUTHOR:** Adja Zoumaro-Djayoon, Leiden University, Netherlands

**CO- AUTHORS:** Diana Behrens, Amy Harms, Thomas Hankemeier

Despite all the progresses made in the identification of molecular alterations related to pancreatic ductal adenocarcinoma cancer (PDAC), effective treatment is still lacking, to reduce the high mortality rate in this cancer. To move forward in pancreatic cancer research, new concepts and methods are required, to find better drug targets and early diagnostics markers. We used metabolomics to investigate the effects of the anti-cancer drugs gemcitabine, abraxane (Nab-paclitaxel) and erlotinib on the metabolism of newly developed patient derived xenografts (PDX). For this purpose, targeted metabolomics platforms that cover metabolites of major metabolic pathways including glycolysis, central metabolism, lipids, amino acids, and signalling lipids (inflammatory mediators), were applied to treated and non-treated tumor tissues from patient derived xenografts of two patients. The comparison between the metabolomics profiles of treated and untreated models, revealed changes in the metabolic profiles. In xenografts derived from one patient, abraxane treatment significantly decreased the levels of amino acids and increased the levels of lipid metabolites, while an increase in the level of sphingomyelins was observed with gemcitabine treatment. However, no significant changes were observed in the metabolic profiles of the second patient upon treatment. Our findings can contribute to the understanding of oncogenic mechanisms in pancreatic ductal adenocarcinoma cancer as well as improve the monitoring of treatments in this cancer.

P-34

The Effects of Omega-3 Supplementation on the Brain Lipidome after Chemotherapy

**PRESENTING AUTHOR:** Rachel Kopec, The Ohio State University, United States

**CO- AUTHORS:** Djawed Bennouna, Melissa Solano, Tonya S. Orchard, Maryam B. Lustberg, A. Courtney DeVries

Breast cancer chemotherapy agents negatively affect long-term brain functioning in some breast cancer survivors. Neuroinflammattory damage may play an important role in changing brain structure or altering signaling, resulting in cognitive impairment. We hypothesized that a diet enriched with long chain omega-3 polyunsaturated fatty acids (n-3 PUFA), would result in a greater inflammation resolving response mediated by specialized pro-resolving mediators (SPMs i.e. omega-3 derived metabolites which attenuate inflammation), and reduce oxidation of hippocampal brain lipids. To determine how n-3 PUFA supplementation may confer protection after chemotherapy, ovariectomized, C57BL/6 mice were fed a diet with or without 2% n-3 PUFA enrichment for 4-6 weeks, followed by a two-injection chemotherapy or vehicle regimen. In study 1, animals (n=120) were sacrificed at 4, 7, and 14 days after the last injection, and targeted HPLC-MS/MS analyses quantitated specialized pro-resolving mediators (SPMs) in whole brain. In study 2, animals (n=80) were sacrificed 7 days after the last injection, and untargeted LC-HRMS lipidomics were performed on the hippocampus. Study 1: SPM resolvin D1 was quantifiable in all samples regardless of treatment or dietary group, but no differences were observed. Study 2: PLS-DA modeling revealed ~500 metabolites driving significant separation between the n-3 PUFA supplemented vs. non-supplemented animals (R2=0.67, Q2=0.64, P-value= 0.014), and that this dietary effect was greater than the effect of chemotherapy 7-days post-chemotherapy treatment. Identification of distinguishing lipids is ongoing. Taken together, the results of studies 1 and 2 suggest that other, non-inflammatory pathways are likely involved in driving this separation between lipids.
<figure><img src="image_33.png" /></figure>

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

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P-35

Urine-NMR metabolomics for screening of advanced colorectal adenoma and early stage colorectal cancer

PRESENTING AUTHOR: Hyuk Nam Kwon, University of Helsinki, Finland

CO-AUTHORS: Eun Ran Kim, Hoonsik Nam, Jae J. Kim, Sunghyouk park, Young-Ho Kim

Although colorectal cancer (CRC) is considered one of the most preventable cancers, no non-invasive, accurate diagnostic tool to screen CRC exists. We explored the potential of urine nuclear magnetic resonance (NMR) metabolomics as a diagnostic tool for early detection of CRC, focusing on advanced adenoma and stage 0 CRC. Urine metabolomics profiles from patients with colorectal neoplasia (CRN; 36 advanced adenomas and 56 CRCs at various stages, n = 92) and healthy controls (normal, n = 156) were analyzed by NMR spectroscopy. Healthy and CRN groups were statistically discriminated using orthogonal projections to latent structure discriminant analysis (opLs-DA). the class prediction model was validated by three-fold cross-validation. The advanced adenoma and stage 0 CRC were grouped together as pre-invasive CRN. The OPLS-DA score plot showed statistically significant discrimination between pre-invasive CRN as well as advanced CRC and healthy controls with a Q2 value of 0.746. In the prediction validation study, the sensitivity and specificity for diagnosing pre-invasive CRN were 96.2% and 95%, respectively. The grades predicted by the OPLS-DA model showed that the areas under the curve were 0.823 for taurine, 0.783 for alanine, and 0.842 for 3-aminoisobutyrate. In multiple receiver operating characteristics curve analyses, taurine, alanine, and 3-aminoisobutyrate were good discriminators for CRC patients. NMR-based urine metabolomics profiles significantly and accurately discriminate patients with pre-invasive CRN as well as advanced CRC from healthy individuals. Urine-NMR metabolomics has potential as a screening tool for accurate diagnosis of pre-invasive CRN.

P-36

Insight the metabolic avidity in the KRAS mutated non-small cell lung cancer cells by flux analysis and biochemical modelling

PRESENTING AUTHOR: Laura Brunelli, Istituto Ricerche Farmacologiche Mario Negri IRCCS, Italy

CO-AUTHORS: Ewelina Węglarz-Tomczak, Elisa Caiola, Mirko Marabese, Giovanna Sestito, Massimo Broggini, Hans Westerhoff, Roberta Pastorelli

Non-small-cell lung cancer (NSCLC) is a heterogeneous disease, with multiple different oncogenic driver mutations. Currently, there are no successful treatment targeting NSCLC KRAS-mutated patients. In NSCLC roughly half of the tumors with activating KRAS genetic lesions also have serine/threonine kinase 11 (LKB1) deletions or inactivating mutations. The presence of LKB1 loss in KRAS-mutant tumor may represent a significant source of heterogeneity and contribute to the worst response to therapy. Since both KRAS and LKB1 lesions have impact on cellular metabolism, it is fundamental to discern the metabolic effects induced by single and concomitant genetic events, in view of the potential exploitation of such metabolic dependencies for novel therapeutic interventions. Using 13C-metabolic flux analysis, we demonstrated how isogenic NSCLC cells harbouring both KRAS/LKB1 alterations were able to exploit the central cellular metabolic routes through a heightened metabolite production compare to the single ones. Further, to recognize such peculiar metabolic behaviour we performed in silico modelling on genome wide metabolic reconstruction. Based on RNA-seq, metabolic enzymes abundance and composition of the medium and using flux balance analyses we predicted metabolic changes. The observed differences in metabolites production were correlated with experimental observations supporting that the enhanced metabolic activity of cells with both genetic lesions rendered the viability of these cells more susceptible to energetic stress such as glycolysis inhibition and/or nutrients limitation than those harboring single lesions. This observation raises the prospect that energy stress may affect NSCLC cells harbouring co-occurring lesions, which may render them more susceptible to cytotoxic drugs.

P-37

Comprehensive evaluation of a one-step sample preparation for global LC-MS lipidomics of cancer cell cultures

PRESENTING AUTHOR: Gillian Mackay, CRUK Beatson Institute, United Kingdom

CO-AUTHORS: Giovanny Rodriguez-Blanco, Victor H Villar, David Sumpton

Lipidomics aims to provide a global analysis of all lipid species present in biological samples. Lipids play an important role in cell membrane integrity, energy storage, and cell signalling, all of which are relevant in cancer development and progression. Standard methods in lipidomics profiling of cell cultures involve biphasic separation using organic solvents such as chloroform or methyl tert-butyl ether to extract the lipids, followed by evaporation and reconstitution in an LC-MS compatible solvent. Some technical issues can arise using this biphasic extraction and reconstitution: we experienced issues with reproducibility between biological replicates and inaccuracy in our normalisation to protein content, an important parameter when comparing cells growing at different rates. In this study, we propose a rapid single step procedure involving simultaneous lipid extraction and protein precipitation from cell culture plates using either isopropanol (IPA) or a mixture of 1:1 butanol/methanol (BuMe). To evaluate the extraction efficiency of IPA and BuMe compared with chloroform/methanol, HepG2 (liver cancer) cells were grown in a standard medium, in a lipid-rich medium and after treatment with a DGAT inhibitor, inhibiting triacylglycerol biosynthesis. Our LC method and mass spectrometry parameters were addressed, as were various methods and software for data analysis. We compared global changes in lipid classes, differences in lipid intensities and the effect of the DGAT inhibitor, with the three different extraction procedures.
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P-38

Investigation of mevalonate pathway by quantitative metabolomics and isotopologue profiling

PRESENTING AUTHOR: Floriant Bellvert, MetaToul-MetaboHUB, France

CO-AUTHORS: Hanna Kulyk-Barbier, Sara Castano-Cerezo, Pierre Millard1, Jean-Charles Portais, Stéphanie Heux, Gilles Truan, Floriant Bellvert.

Mevalonate pathway is an important metabolic pathway which plays a key role in multiple cellular processes. In recent years the mevalonate pathway has become a challenging and, in the meantime, fascinating topic, when a large number of experimental and clinical studies suggested that inhibition of nonsterol isoprenoids might have valuable interest in human pathology. These molecules that are essential for cell growth and differentiation appear to be potential interesting therapeutic targets for many areas of ongoing research: oncology, autoimmune disorders, atherosclerosis, and Alzheimer disease. Thus, functional understanding of their biosynthesis is important key. However, available methods do not yet allow accurate quantification and tracing of stable isotopes incorporation for all the isoprenoids precursors (mevalonate intermediates and prenyl pyrophosphates). We present a complete methodology for functional analysis of isoprenoids biosynthesis, with a novel quantification method based on liquid chromatography coupled to high-resolution mass spectrometry. This workflow covers all the experimental and computational steps from sample collection and preparation to data acquisition and processing. It ensures accurate, absolute quantification (RSD < 20 %) of all mevalonate and prenyl pyrophosphates intermediates with a high sensitivity over a large linear range (from 0.1 to 50 pmol). Determination of their isotopologue distributions in isotopic labeling experiments was performed, opening the way for 13C-metabolic flux analysis of isoprenoids biosynthesis. In conclusion, the described methodology fills one of the last technical gaps for functional studies of isoprenoids biosynthesis and should be applicable to other eukaryotic and prokaryotic (micro)organisms after adaptation of some organism-dependent steps.

P-39

Prospective Serum Metabolomic Profile of Prostate Cancer Risk in African-Americans from Two U.S. Cohorts

PRESENTING AUTHOR: Demetrius Albanes, U.S. National Cancer Institute, United States

CO-AUTHORS: Jiaqi Huang, Stephanie Weinstein, Joshua Sampson, Christopher Haiman, Loic Le Marchand, Tracy Layne

African-American men are under-studied in prostate cancer research despite having substantially higher disease incidence compared to other races. Recent prospective studies conducted primarily among men of European ancestry identified several plasma/serum metabolites associated with prostate cancer risk, including lipids (fatty acids, acylcarnitines, sphingomyelins, inositol, glycerphospholipids, and androgens), dipeptides and gamma-glutamyl amino acids, nucleotides, TCA cycle compounds and antioxidants. We examined the prospective serum metabolomic profile of prostate cancer risk in African-Americans in order to elucidate possible biological mechanisms underlying their greater disease burden. We meta-analyzed two case-control studies nested within the Multiethnic Cohort and Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial cohort (592 cases/592 controls, matched on age, study center, and blood collection date). Samples were analyzed using ultrahigh performance liquid chromatography/tandem mass spectrometry (Metabolon, Inc.) that identified 997 known compounds. Conditional logistic regression estimated ORs and 95% CIs for 1-s.d. increments in metabolite levels that were meta-analyzed using a fixed-effects model. Median time from serum collection to diagnosis was 5 years (maximum 19 years). Metabolites showing the strongest associations with prostate cancer risk (FDR q-value=0.2) were p-cresol glucuronide (1-s.d. OR 0.80, p=0.00045), hypotaurine (1-s.d. OR 1.25, p=0.0006), p-cresol sulfate (1-s.d. OR 0.81, p=0.00078), indolin-2-one (1-s.d. OR 0.81, p=0.00084), asparagine (1-s.d. OR 1.23, p=0.001), indole-3-carboxylic acid (1-s.d. OR 0.80, p=0.002), and taurine (1-s.d. OR 1.21, p=0.002). The metabolomic profile of prostate cancer risk in this investigation of black men suggests an etiologic role for microbiota-related metabolites that differs substantially from metabolites previously identified in populations of European ancestry.

P-40

Radiometabolomics – correlation of metabolomics and PET/MRI imaging data of non-small cell lung cancer patients

PRESENTING AUTHOR: Michal Ciborowski, Medical University of Bialystok, Poland

CO-AUTHORS: Joanna Kisluk, Tomasz Kowalczyk, Ewa Sierko, Joanna Reszec, Malgorzata Mojsak, Karolina Pietrowska, Joanna Godzien, Adam Kretowski, Jacek Niklinski

Lung cancer (LC) remains the leading cause of cancer death worldwide with non-small cell lung cancer (NSCLC) constituting about 85% of all LC cases. Recently positron emission tomography/magnetic resonance imaging (PET/MRI) is actively used to study LC. Measurement of 2-deoxy-2-[18F]-fluoro-D-glucose uptake by tumor reflects its increased rate of aerobic glycolysis. Among others, PET/MRI provides information about tumor size (Metabolic Tumor Volume, MTV) and metabolic activity (Standardized Uptake Value, SUV). Correlation of PET/MRI results with metabolomics data may help to indicate metabolic pathways engaged in tumor growth and activity. Plasma samples of 47 NSCLC patients (65±6 years old, 20 females) were fingerprinted with LC-QTOF-MS. Patients also underwent PET/MRI examination. Pearson correlation (absolute r>0.4 and p≤0.05 were considered significant) was used to evaluate a relation between intensities of metabolites and MTV, SUV maximum and SUV mean values. Several bile acids (r=-0.42-0.51, p=0.0006-0.002), sulfated steroid hormones (r=-0.41-0.55, p=0.00006-0.005), amino acids (r=-0.42-0.58, p=0.00002-0.003), and acylcarnitines (r=-0.42-0.54, p=0.0001-0.003) were found correlated with tumor size and activity. Differences in correlation of metabolites with MTV and SUV values were observed for uric acid (r=-0.36, p=0.01 vs r=-0.44, p=0.001), oleanide (r=0.42, p=0.03 vs r=0.2, p=0.2), anandamide (r=-0.42, p=0.003 vs r=-0.21, p=0.1), and several lysophosphatidylethanolamines (r=-0.4-0.55, p=0.00006-0.001 vs r=-0.25-0.37, p=0.09-0.01). Metabolic activity of tumor affects bile acids, amino acids, steroid hormones and energy metabolism. Tumor growth mainly affects lysophosphatidylethanolamines metabolism. Acknowledgment: The study was funded by the grant from National Centre for Research and Development in the framework of Programme "Prevention practices and treatment of civilization diseases"-STRATEGMED (STRATEGMED2/266484/2/NCBR/2015).
**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-41

Small-molecule mutant isocitrate dehydrogenase inhibitors diminish metabolic differences between mIDH1 and wIDH1 expressing cells

PRESENTING AUTHOR: Ingvild Comfort Hvinden, University of Oxford, Department of Chemistry, United Kingdom

CO-AUTHORS: John Walsby-Tickle, Christopher J. Schofield, James S. O. McCullagh

Oncogenic missense mutations in isocitrate dehydrogenase (IDH) 1 or 2 have been found in at least 13 different cancers. These mutations leads to metabolic and epigenetic perturbations, including a substantial increase in the oncometabolite R-2-hydroxyglutarate (2HG), which is considered key to tumorigenesis. In lower grade gliomas, approximately 70% of tumours express mIDH1 or mIDH2 but they remain challenging to diagnose early and treat; mIDH has emerged as a promising target. The goal of this study was to better understand the effect of small-molecule IDH1 inhibitors (AGI-5198, AGI-120, AGI-881) on altered metabolic pathways in IDH mutant and wild type cells. Glioblastoma cells (LN18) were genetically engineered to express IDH1 R132H; cell metabolism was investigated using anion exchange and reversed phase chromatography coupled to mass spectrometry. Treatment of mIDH cells revealed a substantial decrease in 2HG. Additionally, 2-oxoglutarate, β-citryl-glutamate, saccharopine, 2-aminoadiapate, and oxoadipic acid were elevated upon treatment of mutant cells. The latter three metabolites are intermediates in lysine metabolism, a pathway which appears to be significantly affected in mIDH1 cells. B-citryl-glutamate is an endogenous iron chelator and has been associated with regulation of neuronal cell differentiation. These findings suggest that IDH inhibitors are able to 'normalise' altered mIDH1 metabolism, bringing it closer to wIDH1 metabolism. The consequences of such 'normalisation' are yet to be understood from a therapeutic perspective, but the metabolic adaptations in response to treatment could help identify metabolic targets for therapeutic intervention, e.g. the lysine degradation pathway.

P-42

Predictive biomarker discovery of treatment response in lung cancer: A metabolomic approach

PRESENTING AUTHOR: José Pérez, MEDINA, Spain

CO-AUTHORS: José Pérez del Palacio, Caridad Díaz-Navarro, Leticia Díaz-Beltrán, Ariadna Martín-Blázquez, Daniel Franco, Ana Laura Ortega-Granados, María Ruiz, Mónica Fernández, Capilla De la Torre, Francisco José García-Verdejo, Francisca Vicente, Olga Genilloud, Pedro Sánchez-Rovira

Although the broad range of chemotherapeutic agents approved in the late years, it is a challenge for oncologists to choose which drug or combination of drugs will represent the best option for each individual, since only a portion of patients will respond properly. In this regard a biomarker approach to predict patient response to treatment, may be very helpful in the making decision process. Metabolomics, the unbiased identification and quantification of small molecule metabolites in biological samples, is particularly promising for biomarker development because altered metabolism is considered a hallmark of cancer. In this work, we have investigated the metabolome of an initial set of 115 plasma samples from lung cancer patients by mean of liquid chromatography high resolution mass spectrometry. The obtained data matrix was analyzed according the clinical response to each therapy (neoadjuvant and immunotherapy) in order to search for a predictive molecular signature in each group of patients. As a result, multivariate ROC analysis displayed moderate ability to discriminate between Responder and Non-responder lung cancer patients. We found and tentatively identified 1 compound that was differentially regulated in lung cancer patients with complete clinical response vs. progressive disease patients. This study has been currently increased with a second batch of 100 samples of lung cancer patients with the objective of confirm our previous findings. These results suggest that metabolomics might provide a new era of response biomarkers, more appropriate for monitoring therapy.

P-43

Highly untargeted lipidomics of NSCLC shows differentially abundant lipid classes in cancer vs non-cancer tissue

PRESENTING AUTHOR: Hunter Moseley, University of Kentucky, United States

CO-AUTHORS: Joshua M. Mitchell, Robert M. Flight

Lung cancer is the leading cause of cancer death worldwide and non-small cell lung cancer (NSCLC) represents 85% of newly diagnosed lung cancers. The high mortality rate is due in part to the lack of effective treatment options for advanced disease. Incomplete understanding of NSCLC metabolism at a molecular level limits the development of effective treatments. Ultra-high-resolution Fourier transform mass spectrometry (FTMS) combined with our untargeted assignment tool SMIRFE enable a systematic and less biased examination of NSCLC lipid metabolism. From 86 patients with suspected resectable stage I or IIa primary NSCLC, lipid extracts were prepared from paired disease and non-disease tissue samples and analyzed using FTMS. Pathological examination revealed that the majority of the samples were primary NSCLC. Machine learning was then employed to classify SMIRFE formula assignments into lipid categories, followed by differential abundance analysis. Both sterols and glycerolipids were consistently and significantly upchanged in disease versus non-disease. The significant sterol upchange suggests a possible therapeutic role for statins and nitrogenous bisphosphonates, inhibitors of endogenous sterol biosynthesis, in the treatment of primary NSCLC. Additionally, the sterol esters are consistently and significantly upchanged, suggesting increased SCD1 activity. SCD1 expression is a known negative prognostic indicator for survival in NSCLC. In our study, a large fraction of the NSCLC samples displayed this phenotype, suggesting that this metabolic phenotype is shared across multiple genetic subtypes. Thus, inhibitors of SCD1 and other enzymes involved in the production of this metabolic phenotype could have utility in the treatment of many NSCLC genetic subtypes.
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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-44

What can we learn about differences in metabolic profiles of urinary tract cancers? Multiplatform approach

PRESENTING AUTHOR: Marta Kordalewska, Dept. of Biopharmacetics and Pharmacodynamics, Medical University of Gdansk, Poland

CO-AUTHORS: Julia Jacyna, Renata Wawrzyniak, Marcin Markuszewski, Marcin Matuszewski, Michał Jan Markuszewski

Standard methods utilized in diagnostics of urinary tract cancers require the use of specialist equipment, may cause patients' discomfort and are adopted when disease symptoms are observed, mostly at the late stage of the disease. As Bladder cancer (BCa) and Renal Cell Carcinoma (RCC) constitute ninth and thirteen types of cancer in terms of incidences worldwide, respectively [1], specific and non-invasive diagnostic methods for early diagnosis of BCa and RCC are needed. Urine samples obtained from BCa patients and healthy volunteers were analyzed with the use of LC-MS and GC-MS. The obtained datasets were subjected to deconvolution, filtration and normalization. Afterwards, statistical analysis was utilized to select metabolites that represented significant differences between studied groups. Samples obtained from RCC patients were analyzed in analogical manner. Finally, the identification of selected metabolites was performed with the use of publicly available databases allowing for creation of lists of potential metabolic indicators of BCa and RCC, that were compared for similarities (e.g. altered concentrations of hippuric acid and uridine). The obtained results suggest that urine metabolic fingerprinting could be a powerful tool for metabolic indicators' investigation and searching for explanation of BCa and RCC pathomechanisms at molecular level. Acknowledgements: The project was supported by the National Science Centre grant no. 2015/19/N/NZ7/03397

P-45

Characterization of Plasma-derived Exosomal Proteins Biomarkers in Glioma Patients

PRESENTING AUTHOR: Rashmi Rana, Sir Ganga Ram Hospital, Old Rajinder Nagar, India

CO-AUTHORS: Jyoti Kumari

Exosomes in Glioma are distinctly strong intermediator with ability for flipping the action of neighbouring cells. This becomes more obvious that exosomes have aptitude to encourage the development of pre metastatic niche. As for metastasis to happen, glioma cells need to migrate in a new environment which also requires being favourable for tumor to colonize properly. Their release into the circulation has the potential to inform about tumor status. In-depth proteomic characterization of plasma-derived EVs has been limited by challenges in isolating EVs from protein-abundant biological fluids. We implemented a novel single-step density gradient flotation workflow for efficient and rapid isolation of highly enriched circulating EXO from plasma-derived exosomes. Effective methods for glioma are still in the waiting and there is strong need for high confidence identification of blood-based biomarkers. Exosomes have recently emerged as a novel source of circulatory biomarkers for cancer. We assess the value of exosome proteins as biomarkers for glioma. NTA and TEM confirmed the presence of plasma-derived EXOs isolated by differential centrifugation. Total proteins extracted from plasma-derived EXOs of 40 glioma (grade I, II, III, IV) and 40 healthy subjects was analyzed. FACS analysis to characterized exosomal proteins tetraspanins CD63, CD9 and CD81 was demonstrated to be significantly increased in glioma patients with controls. 1D analysis of exosomal proteins was carried out to identify proteins showing altered levels in glioma cases in comparison to controls. Our findings support the potential of exosomes derived proteins as a source of biomarkers that complement other approaches for tumor assessment.

P-46

Sequential untrageted metabolomics and lipidomic profiling identifies key difference in amino acid and lipid between the bone marrow plasma of MGUS and Multiple Myeloma

PRESENTING AUTHOR: Wilson Gonsalves, Dr., United States

CO-AUTHORS: Kasia Broniowska, Erik Jessen, Xuan-Mai Petterson, Shaji Kumar, Sreekumaran Nair

Multiple myeloma (MM) is a clonal plasma cell malignancy that is incurable and has a devastating clinical course. It is always preceded by an asymptomatic precursor disorder, monoclonal gammopathy of undetermined significance (MGUS). We conducted a prospective assessment of metabolome differences between the bone marrow plasma obtained from patients with MGUS to that of patients with MM. Global metabolite profiling was performed by Metabolon Inc. on the bone marrow plasma of 25 MGUS patients and 25 MM patients using a Waters ACQUITY ultra-performance liquid chromatography (UPLC) and a Thermo Scientific Q-Exactive high resolution/accurate mass spectrometer interfaced with a heated electrospray ionization (HESI-II) source and Orbitrap mass analyzer operated at 35,000 mass resolution. Lipidomics was performed on a Shimazdu LC and the Sciex Selexion-5500 QTRAP. Following log transformation and imputation of missing values, if any, with the minimum observed value for each compound, ANOVA contrasts were used to identify biochemicals that differed significantly between the MGUS and MM groups. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) were able to show group separation based on several distinct classes of metabolites. Overall, it was determined that bone marrow plasma samples obtained from patients diagnosed with MM and MGUS, differed in a number of metabolic readouts, including changes in lipid metabolism, amino acid catabolism, and nucleotide turnover. Verification of these results in an independent cohort is required next to lead to a panel of biomarkers that could aid in identifying possible predictive biomarkers of progression from MGUS to MM.