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Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated, and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers, imputation of missing data, (ii) identification of the main sources of variability through principal component partial R-square (PC-PR2) analysis, (iii) application of linear mixed models to remove unwanted variability, including samples’ originating study and batch, and preserve biological variations while accounting for potential differences in the residual variances across studies. This pipeline was applied to targeted metabolomics data acquired using Biocrates AbsoluteIDQ kits in eight case-control studies nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Comprehensive examination of metabolomics measurements indicated that the pipeline improved the comparability of data across the studies. Our pipeline can be adapted to normalize other molecular data, including biomarkers as well as proteomics data, and could be used for pooling molecular datasets, for example in international consortia, to limit biases introduced by inter-study variability. This versatility of the pipeline makes our work of potential interest to molecular epidemiologists.

Background: A growing body of evidence suggests that alterations of dietary fatty acid (FA) profiles are associated with colorectal cancer risk. However, data from large-scale epidemiologic studies using circulating FA measurements to objectively assess individual FA and FA categories are scarce. Methods: We investigate the association between red blood cell (RBC) membrane FAs and risk of colorectal cancer in a case–control study nested within a large prospective cohort. After a median follow-up of 6.4 years, 1,069 incident colorectal cancer cases were identified and matched to 1,069 controls among participants of the European Prospective Investigation into Cancer and Nutrition (EPIC). The FA composition of RBC phospholipids (in mol%) was analyzed by gas chromatography, and their association with risk of colorectal cancer was estimated by multivariable adjusted conditional logistic regression models. Results: After correction for multiple testing, subjects with higher concentrations of RBC stearic acid were at higher risk for colorectal cancer (OR ¼ 1.23; 95% CI ¼ 1.07–1.42, per 1 mol%). Conversely, colorectal cancer incidence decreased with increasing proportions of RBC n-3 PUFA, particularly eicosapentaenoic acid (0.75; 0.62–0.92, per 1 mol%). The findings for the n-6 PUFA arachidonic acid were inconsistent. Conclusions: The positive association between prediagnostic RBC stearic acid and colorectal cancer reflects putative differences in FA intake and metabolism between cancer cases and matched controls, which deserve further investigation. The inverse relationship between EPA and colorectal cancer is in line with the repeatedly reported protective effect of fish consumption on colorectal cancer risk. Impact: These findings add to the evidence on colorectal cancer prevention.

Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (>520 000 participants), where we identified 129 HCC cases matched 1:1 to controls. We conducted high-resolution untargeted liquid chromatography-mass spectrometry-based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk, of which 14 were unambiguously identified using pure reference standards. Positive HCC-risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, l,l-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids and phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development.

Background Excess bodyweight and related metabolic perturbations have been implicated in kidney cancer aetiology, but the specific molecular mechanisms underlying these relationships are poorly understood. In this study, we sought to identify circulating metabolites that predispose kidney cancer and to evaluate the extent to which they are influenced by body mass index (BMI). Methods and findings We assessed the association between circulating levels of 1,416 metabolites and incident kidney cancer using pre-diagnostic blood samples from up to 1,305 kidney cancer case–control pairs from 5 prospective cohort studies. Cases were diagnosed on average 8 years after blood collection. We found 25 metabolites robustly associated with kidney cancer risk. In particular, 14 glycerophospholipids (GPLs) were inversely associated with risk, including 8 phosphatidylcholines (PCs) and 2 plasmalogens. The PC with the strongest association was PC ae C34:3 with an odds ratio (OR) for 1 standard deviation (SD) increment of 0.75 (95% confidence interval [CI]: 0.68 to 0.83, p = 2.6 × 10−8). In contrast, 4 amino acids, including glutamate (OR for 1 SD = 1.39, 95% CI: 1.20 to 1.60, p = 1.6 × 10−5), were positively associated with risk. Adjusting for BMI partly attenuated the risk association for some—but not all—metabolites, whereas other known risk factors of kidney cancer, such as smoking and alcohol consumption, had minimal impact on the observed associations. A mendelian randomisation (MR) analysis of the influence of BMI on the blood metabolome highlighted that some metabolites associated with kidney cancer risk are influenced by BMI. Specifically, elevated BMI appeared to decrease levels of several GPLs that were also found inversely associated with kidney cancer risk (e.g., −0.17 SD change [ßBMI] in 1-(1-enyl-palmitoyl)-2-linoleoyl-GPC (P-16:0/18:2) levels per SD change in BMI, p = 3.4 × 10−5). BMI was also associated with increased levels of glutamate (ßBMI: 0.12, p = 1.5 × 10−3). While our results were robust across the participating studies, they were limited to study participants of European descent, and it will, therefore, be important to evaluate if our findings can be generalised to populations with different genetic backgrounds. Conclusions This study suggests a potentially important role of the blood metabolome in kidney cancer aetiology by highlighting a wide range of metabolites associated with the risk of developing kidney cancer and the extent to which changes in levels of these metabolites are driven by BMI—the principal modifiable risk factor of kidney cancer., In a case-control study, Florence Guida and colleagues identify metabolites associated with risk of kidney cancer, and use Mendelian randomization techniques to study the role of body mass index in this relationship., Author summary Why was this study done? Several modifiable risk factors have been established for kidney cancer, among which elevated body mass index (BMI) and obesity are central. The biological mechanisms underlying these relationships are poorly understood, but obesity-related metabolic perturbations may be important. What did the researchers do and find? We looked at the association between kidney cancer and the levels of 1,416 metabolites measured in blood on average 8 years before the disease onset. The study included 1,305 kidney cancer cases and 1,305 healthy controls. We found 25 metabolites robustly associated with kidney cancer risk. Specifically, multiple glycerophospholipids (GPLs) were inversely associated with risk, while several amino acids were positively associated with risk. Accounting for BMI highlighted that some—but not all—metabolites associated with kidney cancer risk are influenced by BMI. What do these findings mean? These findings illustrate the potential utility of prospectively measured metabolites in helping us to understand the aetiology of kidney cancer. By examining overlap between the metabolomic profile of prospective risk of kidney cancer and that of modifiable risk factors for the disease—in this case BMI—we can begin to identify biological pathways relevant to disease onset.

Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (>520 000 participants), where we identified 129 HCC cases matched 1:1 to controls. We conducted high-resolution untargeted liquid chromatography-mass spectrometry-based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk, of which 14 were unambiguously identified using pure reference standards. Positive HCC-risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, l,l-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids and phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development. © 2020 UICC

Alcohol consumption is causally linked to several cancers but the evidence for stomach cancer is inconclusive. In our study, the association between long-term alcohol intake and risk of stomach cancer and its subtypes was evaluated. We performed a pooled analysis of data collected at baseline from 491 714 participants in the European Prospective Investigation into Cancer and Nutrition and the Melbourne Collaborative Cohort Study. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated for incident stomach cancer in relation to lifetime alcohol intake and group-based life course intake trajectories, adjusted for potential confounders including Helicobacter pylori infection. In all, 1225 incident stomach cancers (78% noncardia) were diagnosed over 7 094 637 person-years; 984 in 382 957 study participants with lifetime alcohol intake data (5 455 507 person-years). Although lifetime alcohol intake was not associated with overall stomach cancer risk, we observed a weak positive association with noncardia cancer (HR = 1.03, 95% CI: 1.00-1.06 per 10 g/d increment), with a HR of 1.50 (95% CI: 1.08-2.09) for ≥60 g/d compared to 0.1 to 4.9 g/d. A weak inverse association with cardia cancer (HR = 0.93, 95% CI: 0.87-1.00) was also observed. HRs of 1.48 (95% CI: 1.10-1.99) for noncardia and 0.51 (95% CI: 0.26-1.03) for cardia cancer were observed for a life course trajectory characterized by heavy decreasing intake compared to light stable intake (Phomogeneity =.02). These associations did not differ appreciably by smoking or H pylori infection status. Limiting alcohol use during lifetime, particularly avoiding heavy use during early adulthood, might help prevent noncardia stomach cancer. Heterogeneous associations observed for cardia and noncardia cancers may indicate etiologic differences. © 2021 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.

Background Acylcarnitines (ACs) play a major role in fatty acid metabolism and are potential markers of metabolic dysfunction with higher blood concentrations reported in obese and diabetic individuals. Diet, and in particular red and processed meat intake, has been shown to influence AC concentrations but data on the effect of meat consumption on AC concentrations is limited. Objectives To investigate the effect of red and processed meat intake on AC concentrations in plasma and urine using a randomized controlled trial with replication in an observational cohort. Methods In the randomized crossover trial, 12 volunteers successively consumed 2 different diets containing either pork or tofu for 3 d each. A panel of 44 ACs including several oxidized ACs was analyzed by LC-MS in plasma and urine samples collected after the 3-d period. ACs that were associated with pork intake were then measured in urine (n = 474) and serum samples (n = 451) from the European Prospective Investigation into Cancer and nutrition (EPIC) study and tested for associations with habitual red and processed meat intake derived from dietary questionnaires. Results In urine samples from the intervention study, pork intake was positively associated with concentrations of 18 short- and medium-chain ACs. Eleven of these were also positively associated with habitual red and processed meat intake in the EPIC cross-sectional study. In blood, C18:0 was positively associated with red meat intake in both the intervention study (q = 0.004, Student's t-test) and the cross-sectional study (q = 0.033, linear regression). Conclusions AC concentrations in urine and blood were associated with red meat intake in both a highly controlled intervention study and in subjects of a cross-sectional study. Our data on the role of meat intake on this important pathway of fatty acid and energy metabolism may help understanding the role of red meat consumption in the etiology of some chronic diseases. This trial was registered at Clinicaltrials.gov as NCT03354130.

Background & Aims: Colorectal cancer located at different anatomical subsites may have distinct etiologies and risk factors. Previous studies that have examined this hypothesis have yielded inconsistent results, possibly because most studies have been of insufficient size to identify heterogeneous associations with precision. Methods: In the European Prospective Investigation into Cancer and Nutrition study, we used multivariable joint Cox proportional hazards models, which accounted for tumors at different anatomical sites (proximal colon, distal colon, and rectum) as competing risks, to examine the relationships between 14 established/suspected lifestyle, anthropometric, and reproductive/menstrual risk factors with colorectal cancer risk. Heterogeneity across sites was tested using Wald tests. Results: After a median of 14.9 years of follow-up of 521,330 men and women, 6291 colorectal cancer cases occurred. Physical activity was related inversely to proximal colon and distal colon cancer, but not to rectal cancer (P heterogeneity = .03). Height was associated positively with proximal and distal colon cancer only, but not rectal cancer (P heterogeneity = .0001). For men, but not women, heterogeneous relationships were observed for body mass index (P heterogeneity = .008) and waist circumference (P heterogeneity = .03), with weaker positive associations found for rectal cancer, compared with proximal and distal colon cancer. Current smoking was associated with a greater risk of rectal and proximal colon cancer, but not distal colon cancer (P heterogeneity = .05). No heterogeneity by anatomical site was found for alcohol consumption, diabetes, nonsteroidal anti-inflammatory drug use, and reproductive/menstrual factors. Conclusions: The relationships between physical activity, anthropometry, and smoking with colorectal cancer risk differed by subsite, supporting the hypothesis that tumors in different anatomical regions may have distinct etiologies. © 2019 AGA Institute

Background: Metabolomics is a promising molecular tool to identify novel etiologic pathways leading to cancer. Using a targeted approach, we prospectively investigated the associations between metabolite concentrations in plasma and breast cancer risk. Methods: A nested case-control study was established within the European Prospective Investigation into Cancer cohort, which included 1624 first primary incident invasive breast cancer cases (with known estrogen and progesterone receptor and HER2 status) and 1624 matched controls. Metabolites (n = 127, acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexose, sphingolipids) were measured by mass spectrometry in pre-diagnostic plasma samples and tested for associations with breast cancer incidence using multivariable conditional logistic regression. Results: Among women not using hormones at baseline (n = 2248), and after control for multiple tests, concentrations of arginine (odds ratio [OR] per SD = 0.79, 95% confidence interval [CI] = 0.70-0.90), asparagine (OR = 0.83 (0.74-0.92)), and phosphatidylcholines (PCs) ae C36:3 (OR = 0.83 (0.76-0.90)), aa C36:3 (OR = 0.84 (0.77-0.93)), ae C34:2 (OR = 0.85 (0.78-0.94)), ae C36:2 (OR = 0.85 (0.78-0.88)), and ae C38:2 (OR = 0.84 (0.76-0.93)) were inversely associated with breast cancer risk, while the acylcarnitine C2 (OR = 1.23 (1.11-1.35)) was positively associated with disease risk. In the overall population, C2 (OR = 1.15 (1.06-1.24)) and PC ae C36:3 (OR = 0.88 (0.82-0.95)) were associated with risk of breast cancer, and these relationships did not differ by breast cancer subtype, age at diagnosis, fasting status, menopausal status, or adiposity. Conclusions: These findings point to potentially novel pathways and biomarkers of breast cancer development. Results warrant replication in other epidemiological studies. © 2019 The Author(s).

Background: Accurate assessment of polyphenol intakes is needed in epidemiologic research in order to study their health effects, and this can be particularly challenging in international study settings. Objective: The purpose of this work is to describe the procedures to prepare a comprehensive polyphenol food-composition database that was used to calculate standardized polyphenol intakes from 24-h diet recalls (24HDRs) and dietary questionnaires (DQs) in the European Prospective Investigation into Cancer and Nutrition (EPIC). Design: With the use of the comparable food classification and facetdescriptor system of the computerized 24HDR program EPIC-Soft (renamed GloboDiet), foods reported in the 24HDR (n = 74,626) were first aggregated following a stepwise process. Multi-ingredient and generic foods were broken down into ingredients or morespecific foods with consideration of regional consumption habits before matching to foods in the Phenol-Explorer database. Foodcomposition data were adjusted by using selected retention factors curated in Phenol-Explorer. DQ foods (n = 13,946) were matched to a generated EPIC 24HDR polyphenol-composition database before calculation of daily intakes from the 24HDR and DQ. Results: Food matching yielded 2.0% and 2.7% of foods with missing polyphenol content in the 24HDR and DQ food data sets, respectively. Process-specific retention factors for 42 different polyphenol compounds were applied to adjust the polyphenol content in 35 prioritized Phenol-Explorer foods, thereby adjusting the polyphenol content in 70% of all of the prepared 24 food occurrences. A detailed food-composition database was finally generated for 437 polyphenols in 19,899 aggregated raw and prepared foods reported by 10 EPIC countries in the 24HDR. Conclusions: An efficient procedure was developed to build the most-comprehensive food-composition database for polyphenols, thereby standardizing the calculations of dietary polyphenol intakes obtained from different dietary assessment methods and European populations. The whole database is accessible online. This procedure could equally be used for other food constituents and in other cohorts. © 2018 American Society for Nutrition. All rights reserved.

Polyphenols may play a chemopreventive role in colorectal cancer (CRC); however, epidemiological evidence supporting a role for intake of individual polyphenol classes, other than flavonoids is insufficient. We evaluated the association between dietary intakes of total and individual classes and subclasses of polyphenols and CRC risk and its main subsites, colon and rectum, within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. The cohort included 476,160 men and women from 10 European countries. During a mean follow-up of 14 years, there were 5991 incident CRC cases, of which 3897 were in the colon and 2094 were in the rectum. Polyphenol intake was estimated using validated centre/country specific dietary questionnaires and the Phenol-Explorer database. In multivariable-adjusted Cox regression models, a doubling in total dietary polyphenol intake was not associated with CRC risk in women (HR log2 = 1.06, 95% CI 0.99–1.14) or in men (HR log2 = 0.97, 95% CI 0.90–1.05), respectively. Phenolic acid intake, highly correlated with coffee consumption, was inversely associated with colon cancer in men (HR log2 = 0.91, 95% CI 0.85–0.97) and positively associated with rectal cancer in women (HR log2 = 1.10, 95% CI 1.02–1.19); although associations did not exceed the Bonferroni threshold for significance. Intake of other polyphenol classes was not related to colorectal, colon or rectal cancer risks. Our study suggests a possible inverse association between phenolic acid intake and colon cancer risk in men and positive with rectal cancer risk in women. © 2018, Springer Science+Business Media B.V., part of Springer Nature.

In vitro studies have shown several beneficial properties of resveratrol. Epidemiological evidence is still scarce, probably because of the difficulty in estimating resveratrol exposure accurately. The current study aimed to assess the relationships between acute and habitual dietary resveratrol and wine intake and urinary resveratrol excretion in a European population. A stratified random subsample of 475 men and women from four countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) cross-sectional study, who had provided 24-h urine samples and completed a 24-h dietary recall (24-HDR) on the same day, were included. Acute and habitual dietary data were collected using standardised 24-HDR software and a validated country-specific dietary questionnaire, respectively. Phenol-Explorer was used to estimate the intake of resveratrol and other stilbenes. Urinary resveratrol was analysed using tandem MS. Spearman's correlation coefficients between estimated dietary intakes of resveratrol and other stilbenes and consumption of wine, their main food source, were very high (r>0·9) when measured using dietary questionnaires and were slightly lower with 24-HDR (r>0·8). Partial Spearman's correlations between urinary resveratrol excretion and intake of resveratrol, total stilbenes or wine were found to be higher when using the 24-HDR (R2 partial approximately 0·6) than when using the dietary questionnaires (R2 partial approximately 0·5). Moderate to high correlations between dietary resveratrol, total stilbenes and wine, and urinary resveratrol concentrations were observed. These support the earlier findings that 24-h urinary resveratrol is an effective biomarker of both resveratrol and wine intakes. These correlations also support the validity of the estimation of resveratrol intake using the dietary questionnaire and Phenol-Explorer. © The Authors 2017.

Présentation Claudine Manach; International audience

communication orale : Claudine Manach The Second International Congress of Translational Research in Human Nutrition is organised by the Research Centre in Human Nutrition (CRNH) of Auvergne, of which INRA is a member, in collaboration with NuGO, European Association of universities and research institutes in the field of nutrigenomics.communication orale : Claudine ManachThe Second International Congress of Translational Research in Human Nutrition is organised by the Research Centre in Human Nutrition (CRNH) of Auvergne, of which INRA is a member, in collaboration with NuGO, European Association of universities and research institutes in the field of nutrigenomics.; The purpose of dietary assessment is to estimate usual and recent intake of foods, nutrients, bioactive compounds and food contaminants for exploration of associations with health outcomes and monitoring of population nutritional status. These data are still extremely difficult to obtain. Methods currently used are based on dietary questionnaires which have inherent limitations linked to self-reporting. A complementary approach to questionnaires is the use of biomarkers. However, only a few biomarkers have been properly validated, which do not cover the wide range offoods consumed. Metabolomics has emerged as a promising approach to discover nutritional biomarkers. Typically, plasma or urine samples collected before and after acute intake of a specific food are profiled using NMR or high resolution Mass Spectrometry (MS) and compared usingmultivariate statistics to pinpoint the signals reflecting the consumption of the target food. In a proof-of-concept study on citrus, we showed that urine profiling of cohort subjects stratified by consumption could be a more effective strategy for discovery of sensitive biomarkers of intake.

Présentation poster : Y. Fillâtre The Second International Congress of Translational Research in Human Nutrition is organised by the Research Centre in Human Nutrition (CRNH) of Auvergne, of which INRA is a member, in collaboration with NuGO, European Association of universities and research institutes in the field of nutrigenomics ANR Phenomenep ALIA-2010-007 Conseil Regional Auvergne-FEDER post-doc grantPrésentation poster : Y. FillâtreThe Second International Congress of Translational Research in Human Nutrition is organised by the Research Centre in Human Nutrition (CRNH) of Auvergne, of which INRA is a member, in collaboration with NuGO, European Association of universities and research institutes in the field of nutrigenomicsANR Phenomenep ALIA-2010-007 Conseil Regional Auvergne-FEDER post-doc grant; As part of the ANR PhenoMeNEp project, non-targeted profiling is used to identify potential biomarkers of plant food consumption. Using 24 hour dietary recall and food frequency questionnaire data, 144 high (median 974 grams/day) and 66 low (median 305 grams/day) consumers of fruit and vegetables were selected from the French SU.VI.MAX2 cohort. Morning spot urine samples from each subject

Presenting author: J.A. Rothwell We gratefully acknowledge Danone Research, the French National Institute of Cancer and the University of Barcelona for financing the project.Presenting author: J.A. Rothwell We gratefully acknowledge Danone Research, the French National Institute of Cancer and the University of Barcelona for financing the project.; Phenol-Explorer is an open-access web database on polyphenols, a major group ofphytochemicals abundant in plant foods. Version 2.0 of the database was released in late 2011 andincludes comprehensive qualitative and quantitative data on the ‘polyphenol metabolome’ (i.e. allmetabolites derived from the over 500 polyphenols known in foods) in humans and experimentalanimals. Such databases are necessary for the screening of metabolomic profiles and theidentification of potential biomarkers of food consumption. The aim of this study was to analysethese new data to characterize and visualize the polyphenol metabolome. The update wasimplemented by the compilation of data on 383 polyphenol metabolites from 221 originalintervention studies. Research articles were first screened for suitability using pre-defined criteriaand then entered into a relational database via Microsoft Access. The polyphenol metabolome wasthen analyzed via a series of database queries and open-source visualization software. Data weremainly obtained in human and rat models, and profiles of metabolites were similar between thesespecies. The highest Cmax values (maximum plasma concentration) were found in rats, as higherdoses of pure polyphenols could be administered, although in both species, administration of purepolyphenols or polyphenol supplements led to much higher plasma concentrations thanadministration of foods. Conversely, Tmax (time to reach Cmax) was species-dependent and alwaysshorter in the rat. Additionally, the ensemble of all studies administering pure compounds to humansand animals allowed an insight into precursor-metabolite specificity. 5-O-Caffeoylquinic acid,catechin and epicatechin gave rise to the broadest range of metabolites, while hippuric, ferulic, 4-hydroxybenzoic, dihydrocaffeic and vanillic acids were the metabolites derived from the largestnumber of precursors. Knowledge of polyphenol metabolism is crucial to understanding their in vivobioactivities and the polyphenol metabolome is an important component of the information-richfood metabolome, which encompasses all metabolites derived from exposure to the diet.We gratefully acknowledge Danone Research, the French National Institute of Cancer and theUniversity of Barcelona for financing the project.

Présentation poster : Fillâtre Yoann The Second International Congress of Translational Research in Human Nutrition is organised by the Research Centre in Human Nutrition (CRNH) of Auvergne, of which INRA is a member, in collaboration with NuGO, European Association of universities and research institutes in the field of nutrigenomics; National audience

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