Patrick Borel
email: patrick.borel@univ-amu.fr

Charles Desmarchelier

Marion Nowicki

Romain Bott

Lycopene bioavailability

Keywords: carotenoid, absorption, single nucleotide polymorphisms, nutrigenetic, genetic polymorphisms

come

Introduction

Lycopene (LYC) is the red pigment found in tomatoes and tomato products. It is the carotenoid found at the highest levels in the blood of Americans and the second one in the blood of Europeans. Its protective role against the development of prostate cancer and cardiovascular diseases has been suggested [START_REF] Story | An update on the health effects of tomato lycopene[END_REF][START_REF] Mordente | Lycopene and cardiovascular diseases: an update[END_REF][START_REF] Bohm | Lycopene and heart health[END_REF][START_REF] Giovannucci | Tomatoes, tomato-based products, lycopene, and cancer: Review of the epidemiologic literature[END_REF][START_REF] Viuda-Martos | Human health benefits of lycopene and its application to meat products: a review[END_REF][START_REF] Biddle | Lycopene Dietary Intervention: A Pilot Study in Patients With Heart Failure[END_REF] but the mechanisms involved have yet to be fully elucidated. Indeed, although LYC's potential as an antioxidant is well characterized in vitro [START_REF] Kelkel | Antioxidant and antiproliferative properties of lycopene[END_REF], there is evidence that its biological effects could also be mediated by metabolic products of LYC [START_REF] Kopec | Identification and quantification of apo-lycopenals in fruits, vegetables, and human plasma[END_REF][START_REF] Erdman | Are the health attributes of lycopene related to its antioxidant function?[END_REF][START_REF] Lindshield | Lycopenoids: are lycopene metabolites bioactive?[END_REF][START_REF] Mein | Biological activity of lycopene metabolites: implications for cancer prevention[END_REF], a hypothesis supported by the results of recent molecular studies [START_REF] Mein | Biological activity of lycopene metabolites: implications for cancer prevention[END_REF][START_REF] Gouranton | Lycopene inhibits proinflammatory cytokine and chemokine expression in adipose tissue[END_REF][START_REF] Aydemir | Lycopene-derived bioactive retinoic acid receptors/retinoid-X receptors-activating metabolites may be relevant for lycopene's anti-cancer potential[END_REF][START_REF] Gouranton | Apo-10'-lycopenoic acid impacts adipose tissue biology via the retinoic acid receptors[END_REF].

LYC digestion begins in the gastrointestinal lumen where digestive enzymes can modulate its bioaccessibility by facilitating its release from the food matrix to micelles [START_REF] Wang | Lycopene metabolism and its biological significance[END_REF][START_REF] Yeum | Carotenoid bioavailability and bioconversion[END_REF][START_REF] Borel | Factors affecting intestinal absorption of highly lipophilic food microconstituents (fat-soluble vitamins, carotenoids and phytosterols)[END_REF]. Micelles then carry LYC to the apical side of the enterocyte. LYC uptake is not only passive, as previously thought, [START_REF] Diwadkar-Navsariwala | A physiological pharmacokinetic model describing the disposition of lycopene in healthy men[END_REF] but its transport is also facilitated by two membrane proteins, SR-BI (scavenger receptor class B type I) [START_REF] Moussa | Lycopene absorption in human intestinal cells and in mice involves scavenger receptor class B type I but not Niemann-Pick C1-like 1[END_REF], encoded by SCARB1, and CD36 (cluster determinant 36) [START_REF] Moussa | CD36 is involved in lycopene and lutein uptake by adipocytes and adipose tissue cultures[END_REF]. Following uptake, it is possible that a portion of LYC may be metabolized. Indeed, enterocytes contain two enzymes with the potential to cleave LYC. The first one, BCO1 (β-carotene 15,15' oxygenase-1), is a dioxygenase [START_REF] Dela Sena | The human enzyme that converts dietary provitamin A carotenoids to vitamin A is a dioxygenase[END_REF] that catalyzes the oxidative cleavage of LYC with an efficiency similar to that of β-carotene [START_REF] Dela Sena | Substrate specificity of purified recombinant human beta-carotene 15,15'-oxygenase (BCO1)[END_REF], and which has been associated with blood LYC status [START_REF] Ferrucci | Common Variation in the beta-Carotene 15,15'-Monooxygenase 1 Gene Affects Circulating Levels of Carotenoids: A Genome-Wide Association Study[END_REF]. The second enzyme, BCO2 (β-carotene-9,10'oxygenase), has been previously suggested to be the main LYC-cleaving enzyme [START_REF] Lindshield | Lycopenoids: are lycopene metabolites bioactive?[END_REF].

Regardless of possible metabolism, the fraction of parent LYC remaining in the enterocyte is transported within the cell to the site where it is incorporated into chylomicrons (CM). The mechanism of this transport is not known, but proteins involved in intracellular transport of lipids have been suggested to be involved [START_REF] Reboul | Proteins involved in uptake, intracellular transport and basolateral secretion of fat-soluble vitamins and carotenoids by mammalian enterocytes[END_REF]. LYC-containing CM are secreted into the lymph, and then enter the bloodstream. LYC is assumed to stay within these lipoproteins and to follow the fate of CM which is ultimately taken up by the hepatocytes [START_REF] Dallinga-Thie | The metabolism of triglyceride-rich lipoproteins revisited: new players, new insight[END_REF].

Clinical trials dedicated to the study of LYC bioavailability have reported high interindividual variability in blood and tissue LYC concentration in response to LYC intake [START_REF] Diwadkar-Navsariwala | A physiological pharmacokinetic model describing the disposition of lycopene in healthy men[END_REF][START_REF] Stahl | Uptake of lycopene and its geometrical isomers is greater from heatprocessed than from unprocessed tomato juice in humans[END_REF][START_REF] Bowen | Variability of Serum Carotenoids in Reponse to Controlled Diets Containing Six Servings of Fruits and Vegetables per day[END_REF][START_REF] Johnson | Ingestion by men of a combined dose of beta-carotene and lycopene does not affect the absorption of beta-carotene but improves that of lycopene[END_REF][START_REF] O'neill | Intestinal absorption of -carotene, lycopene and lutein in men and women following a standard meal: response curves in the triacylglycerolrich lipoprotein fraction[END_REF][START_REF] Wang | Strong and weak plasma response to dietary carotenoids identified by cluster analysis and linked to beta-carotene 15,15'monooxygenase 1 single nucleotide polymorphisms[END_REF]. Genetic variations between individuals may provide a partial explanation of this phenomenon [START_REF] Borel | Genetic variations involved in interindividual variability in carotenoid status[END_REF][START_REF] Moran | Complex interactions between dietary and genetic factors impact lycopene metabolism and distribution[END_REF]. Some genetic polymorphisms have been shown to be associated with the variability in fasting blood LYC concentrations [START_REF] Ferrucci | Common Variation in the beta-Carotene 15,15'-Monooxygenase 1 Gene Affects Circulating Levels of Carotenoids: A Genome-Wide Association Study[END_REF][START_REF] Wang | Strong and weak plasma response to dietary carotenoids identified by cluster analysis and linked to beta-carotene 15,15'monooxygenase 1 single nucleotide polymorphisms[END_REF][START_REF] Ortega | Influence of apolipoprotein E genotype on fat-soluble plasma antioxidants in Spanish children[END_REF][START_REF] Borel | Human plasma levels of vitamin E and carotenoids are associated with genetic polymorphisms in genes involved in lipid metabolism[END_REF][START_REF] Borel | Human fasting plasma concentrations of vitamin E and carotenoids, and their association with genetic variants in apo C-III, cholesteryl ester transfer protein, hepatic lipase, intestinal fatty acid binding protein and microsomal triacylglycerol transfer protein[END_REF][START_REF] Zubair | Genetic variation predicts serum lycopene concentrations in a multiethnic population of postmenopausal women[END_REF], and yet only one study has attempted to assess the role of genetic polymorphisms involved in the variability in blood LYC concentration following a LYC load [START_REF] Wang | Strong and weak plasma response to dietary carotenoids identified by cluster analysis and linked to beta-carotene 15,15'monooxygenase 1 single nucleotide polymorphisms[END_REF]. Only two SNPs in BCO1 have been previously

shown to be associated with the variability in LYC bioavailability [START_REF] Wang | Strong and weak plasma response to dietary carotenoids identified by cluster analysis and linked to beta-carotene 15,15'monooxygenase 1 single nucleotide polymorphisms[END_REF]. While promising, the small number of candidate genes previously investigated calls for more studies to explain the variation in a phenotype that is likely affected by numerous environmental and genetic factors [START_REF] Borel | Genetic variations involved in interindividual variability in carotenoid status[END_REF]. In fact, we have recently demonstrated that the bioavailability of the carotenoid lutein is a complex phenotype that is not modulated by any single gene, but by the additive effects several gene SNPs [START_REF] Borel | Interindividual variability of lutein bioavailability in healthy men: characterization, genetic variants involved, and relation with fasting plasma lutein concentration[END_REF]. Thus, the aim of this study was to identify the combination of SNPs associated with the variability in LYC bioavailability.

Subjects and Methods

Subject number and characteristics

Thirty five healthy, nonobese, nonsmoking male subjects were recruited for the study.

Subjects presented with normal energy consumption, i.e. ≈ 2500 kcal/d and drank ≤ 2% alcohol as total energy. They had no history of chronic disease, hyperlipidemia, hyperglycemia, and were not taking any medication that might affect LYC or lipid metabolism (e.g. tetrahydrolipstatin, ezetimibe, phytosterols, cholestyramine, fibrates, etc.) during the month prior to the study or during the study period. Because of the relatively large volume of blood that was drawn during the study, subjects were required to have a blood hemoglobin concentration >1.3 g/L as inclusion criteria. The study was approved by the regional committee on human experimentation (N°2008-A01354-51, Comité de Protection des Personnes Sud Méditerranée I, France). The procedures followed were in accordance with the Helsinki Declaration of 1975 as revised in 1983. The objectives and requirements of the study were fully explained to all participants before beginning the study, and informed written consent was obtained from each subject. Two subjects left the study for personal reasons before participating in the postprandial experiment, leaving 33 subjects whose baseline characteristics are reported in Table 1. Note that the fasting plasma LYC concentration of these subjects was relatively high as compared to previous reported data [START_REF] Porrini | What are typical lycopene intakes?[END_REF] suggesting that these subjects regularly consumed tomatoes and tomato products.

DNA preparation and genotyping methods

An average of 25 µg of DNA was isolated from a saliva sample from each subject using the Oragene kit (DNA Genotek Inc., Kanata, ON, Canada) as described in detail previously [START_REF] Hansen | Collection of blood, saliva, and buccal cell samples in a pilot study on the Danish nurse cohort: comparison of the response rate and quality of genomic DNA[END_REF]. DNA concentration and purity were checked by spectrophotometry at 260 nm and 280 nm (Nanodrop ND1000, Thermo Scientific, Villebon sur Yvette, France). All genotyping procedures were carried out by Integragen (Evry, France). Concerning the whole genome genotyping, the procedure was as follows: 200 ng of DNA was hybridized overnight to HumanOmniExpress BeadChips (Illumina, San Diego, CA, USA), allowing the analysis of approximately 7.33 x 10 5 SNPs per DNA sample. Unhybridized and non-specifically hybridized DNA was washed out. The BeadChips were then stained and scanned on an Illumina iScan. Detailed methods are provided in the Infinium HD Assay Ultra Protocol Guide from Illumina. Concerning the 40 other SNPs (see "Choice of candidate genes"), they were genotyped as previously described [START_REF] Lecompte | Polymorphisms in the CD36/FAT gene are associated with plasma vitamin E levels in humans[END_REF].

Postprandial experiments

Subjects were asked to refrain from consuming LYC-rich foods (tomatoes, tomato products, foods rich in tomato, watermelon) for 48 h before the postprandial clinic visit. In addition, the day prior to the visit, they were asked to eat dinner between 7 and 8 p.m., without any alcohol intake. They were also asked to abstain from consuming any food or beverage other than water after the diner and until the clinic visit. After the overnight fast, they arrived at the local Center for Clinical Investigation (la Conception Hospital, Marseille, France) and consumed a test meal including 100 g of tomato puree purchased from a local supermarket providing 9.7 mg all-trans LYC as measured by high performance liquid chromatography (HPLC). The puree also contained around 0.5 mg cis isomers of LYC as evaluated by the relative peak area of all the cis-isomers (4 peaks identified) as compared to the peak area of the all-trans isomer in the HPLC chromatograms. This LYC dose allowed us to deliver about twice the mean dietary intake of LYC in France and a LYC dose close to daily intake in the United states [START_REF] Wang | Strong and weak plasma response to dietary carotenoids identified by cluster analysis and linked to beta-carotene 15,15'monooxygenase 1 single nucleotide polymorphisms[END_REF][START_REF] Porrini | What are typical lycopene intakes?[END_REF]. The remainder of the test meal consisted of semolina (70 g) cooked in 200 mL of hot water, white bread (40 g), egg whites (60 g), peanut oil (50 g), and mineral water (330 mL). The subjects were asked to consume the meal at a steady pace, with half of the meal consumed in the first 10 min, and the remainder of the meal consumed in the 20 next min. This pacing should have ultimately reduced anyvariability in gastric emptying due to variation in rates of intake. No other food was permitted over the following 8 h, but subjects were permitted to finish the remainder of the 330 mL of water they had not drunk during the meal. A fasting baseline blood sample was drawn before administration of the meal as well as at 2, 3, 4, 5, 6 and 8 h after meal consumption. Blood was taken up into evacuated tubes containing K-EDTA. The tubes were immediately placed into an ice-water bath and covered with aluminum foil to avoid light exposure. Plasma was isolated by centrifugation (10 min at 4 °C and 878 g) within 2 h following collection.

CM preparation

Plasma (6 mL) was overlaid with 0.9% NaCl solution (4.5 mL) and centrifuged for 28 min at 130,000 x g at 10 °C using a SW41Ti rotor (Beckman Coulter, Villepinte, France) in a Thermo Sorvall WX100 ultracentrifuge (Thermo Scientific, Saint Herblain, France). The upper phase, containing mainly CM and large CM remnants [START_REF] Luchoomun | Assembly and secretion of chylomicrons by differentiated Caco-2 cells. Nascent triglycerides and preformed phospholipids are preferentially used for lipoprotein assembly[END_REF][START_REF] Richelle | The proportion of lycopene isomers in human plasma is modulated by lycopene isomer profile in the meal but not by lycopene preparation[END_REF], was collected.

Immediately after recovery, CM were stored at -80 °C prior to LYC analysis.

CM LYC extraction and analysis

Total CM LYC, a mixture of all-trans and LYC cis isomers [START_REF] Richelle | The proportion of lycopene isomers in human plasma is modulated by lycopene isomer profile in the meal but not by lycopene preparation[END_REF][START_REF] Richelle | Lycopene isomerisation takes place within enterocytes during absorption in human subjects[END_REF], was extracted and analyzed as follows. Briefly, up to 2 mL of CM was deproteinated by adding one volume of ethanol which also contained apo-8'-carotenal as an internal standard. After adding two volumes of hexane, the mixture was vortexed for 10 min and centrifuged at 500 x g for 10 min at 4 °C. The upper phase (containing LYC) was collected and the sample was extracted a second time with hexane following the same procedure. The hexane phases were pooled and evaporated completely under nitrogen gas. The dried extract was then redissolved in 200 µL of a dichloromethane/methanol mixture (65:35, v/v). All extractions were performed at room temperature under yellow light to minimize light-induced damage. A volume of 90 µL was injected for HPLC analysis. Separation was achieved using a 10 × 4.0 mm, 2 µm Modulo-Cart QS guard column (Interchim, Montluçon, France) followed by a 250 × 4.6 mm internal diameter, 5 µm particle size, YMC C30 column (Interchim) held at 35 °C. The mobile phase was composed of HPLC grade methanol (A), methyl tert-butyl ether (B) and water (C). A linear gradient of 96% A, 2% B, 2% C at t = 0 to 18% A, 80% B, 2% C at t = 27 min at a flow rate of 1 mL/min was used. The HPLC system consisted of a pump (Waters 2690) connected in-line with a photodiode-array detector (Waters 2996) (Waters, Saint Quentin en Yvelines, France). LYC was identified via UV-Vis spectra and retention time coincident with authentic standard (generous gift of DSM LTD, Basel, Switzerland) and quantitated at 472 nm. The consecutive peaks, which contained all-trans LYC and cis-LYC isomers, were integrated together to obtain the sum of all LYC isomers. Integration was performed using Chromeleon software (version 6.80, Dionex, Villebon sur Yvette, France), and quantitation was performed by comparing sample peak area with all-trans LYC calibration curves. Values were corrected by extraction efficiency based on the recovery of the internal standard.

Calculations

The trapezoidal approximation rule was used to calculate the postprandial plasma CM LYC response, i.e. the area of the postprandial plasma CM LYC concentration over 8 hours (AUC). Calculated AUCs were baseline-corrected using the fasting plasma CM LYC concentration measured in each subject.

Choice of candidate genes

The candidate genes included those whose encoded proteins have been shown by in vitro methods to be involved in cellular uptake of LYC, i.e. SCARB1 (scavenger receptor class B, member 1) [START_REF] Moussa | Lycopene absorption in human intestinal cells and in mice involves scavenger receptor class B type I but not Niemann-Pick C1-like 1[END_REF] and CD36 (cluster of differenciation 36) [START_REF] Moussa | CD36 is involved in lycopene and lutein uptake by adipocytes and adipose tissue cultures[END_REF], genes that are suspected to be involved, directly or indirectly, in enterocyte LYC metabolism, e.g. L-FABP (liver-fatty acid binding protein) [START_REF] Reboul | Proteins involved in uptake, intracellular transport and basolateral secretion of fat-soluble vitamins and carotenoids by mammalian enterocytes[END_REF], MTTP (microsomal triglyceride transfer protein), and genes that have been associated in genome-wide association studies [START_REF] Ferrucci | Common Variation in the beta-Carotene 15,15'-Monooxygenase 1 Gene Affects Circulating Levels of Carotenoids: A Genome-Wide Association Study[END_REF][START_REF] Zubair | Genetic variation predicts serum lycopene concentrations in a multiethnic population of postmenopausal women[END_REF] or candidate gene association studies [START_REF] Wang | Strong and weak plasma response to dietary carotenoids identified by cluster analysis and linked to beta-carotene 15,15'monooxygenase 1 single nucleotide polymorphisms[END_REF][START_REF] Ortega | Influence of apolipoprotein E genotype on fat-soluble plasma antioxidants in Spanish children[END_REF][START_REF] Borel | Human plasma levels of vitamin E and carotenoids are associated with genetic polymorphisms in genes involved in lipid metabolism[END_REF][START_REF] Borel | Human fasting plasma concentrations of vitamin E and carotenoids, and their association with genetic variants in apo C-III, cholesteryl ester transfer protein, hepatic lipase, intestinal fatty acid binding protein and microsomal triacylglycerol transfer protein[END_REF] with blood LYC concentration. This resulted in the selection of 26 genes (Supplementary table 1), representing 2202 SNPs on the arrays. In addition, we added 30 SNPs in 23 genes that we have recently found to be associated with the postprandial CM triacylglycerol response in the same group of subjects [START_REF] Desmarchelier | The postprandial chylomicron triacylglycerol response to dietary fat in healthy male adults is significantly explained by a combination of single nucleotide polymorphisms in genes involved in triacylglycerol metabolism[END_REF]. Indeed, CMs are the main blood carrier of newly absorbed LYC and we hypothesized that genetic variants that affect the secretion/clearance of CMs in the postprandial period likely affect the postprandial blood response in LYC. We also added 40 SNPs that have been associated, in previous publications, with lipid metabolism (Supplementary table 2). After genotyping of the subjects (see above), SNPs whose genotype call rate was <95%, or SNPs presenting a significant departure from Hardy-Weinberg equilibrium (P<0.05 following the Chi-squared test), were excluded from all subsequent analysis (387 SNPs excluded; 1885 SNPs left for the PLS regression analysis).

-Multivariate analysis with partial least squares regression

In order to identify SNPs associated with the variability in the postprandial plasma CM LYC response, we employed partial least squares regression (PLS). PLS is a multivariate statistical tool often used for chemometric [START_REF] Eriksson | Using chemometrics for navigating in the large data sets of genomics, proteomics, and metabonomics (gpm)[END_REF] and spectrometric modeling, and which has recently been applied to SNP-based predictions by our group [START_REF] Desmarchelier | The postprandial chylomicron triacylglycerol response to dietary fat in healthy male adults is significantly explained by a combination of single nucleotide polymorphisms in genes involved in triacylglycerol metabolism[END_REF][START_REF] Borel | Genetic variants in BCMO1 and CD36 are associated with plasma lutein concentrations and macular pigment optical density in humans[END_REF] and others [START_REF] Cao | Sparse PLS discriminant analysis: biologically relevant feature selection and graphical displays for multiclass problems[END_REF][START_REF] Long | Dimension reduction and variable selection for genomic selection: application to predicting milk yield in Holsteins[END_REF]. Due to the large number of SNPs compared with the low number of subjects and multicollinearity between SNPs, PLS regression is used to identify the best combination of variables (i.e. SNPs) that are predictive of another variable, in this case the postprandial CM LYC response.

Since the inheritance model could not be known for the 1885 SNPs entered in the PLS regression analysis, a general genetic model was assumed, i.e. the three genotypes of each SNP were treated as separate categories with no assumption made about the effect conferred by homozygous or heterozygous alleles on the phenotype. Different PLS regression models were built using increasing variable in the projection (VIP) threshold values. The model maximizing the explained (R²) and the predicted variance (Q²), and validated following crossvalidation ANOVA, was selected. Additional validation procedures of the PLS regression models [START_REF] Borel | Interindividual variability of lutein bioavailability in healthy men: characterization, genetic variants involved, and relation with fasting plasma lutein concentration[END_REF][START_REF] Desmarchelier | The postprandial chylomicron triacylglycerol response to dietary fat in healthy male adults is significantly explained by a combination of single nucleotide polymorphisms in genes involved in triacylglycerol metabolism[END_REF][START_REF] Borel | Can genetic variability in alpha-tocopherol bioavailability explain the heterogeneous response to alpha-tocopherol supplements?[END_REF] were also performed and are described in Supplementary Methods.

Simca-P12 software (Umetrics, Umeå, Sweden) was used for all multivariate data analyses and modeling.

Univariate analysis

In a second approach, we performed univariate analyses to compare the postprandial plasma CM LYC response between subgroups of subjects who bore different genotypes for the SNPs selected in the PLS regression model. Differences obtained in the different genotype subgroups were analyzed using Student's t-test with the Benjamini-Hochberg correction, using QVALUE software [START_REF] Storey | A direct approach to false discovery rates[END_REF]. For all tests, an adjusted P-value<0.05 was considered significant.

Results

Interindividual variability in postprandial plasma CM LYC responses to the test meal

Figure 1 shows the postprandial CM LYC response after consumption of the test meal containing tomato puree. The CV of the postprandial plasma CM LYC response, called "LYC response" hereafter in the manuscript, was 70%, as illustrated in Figure 2.

Correlation between the LYC response to the test meal and the fasting plasma LYC concentration

In order to assess whether the fasting plasma LYC concentration, previously found to be a good marker of LYC status, was related to LYC bioavailability, we calculated the correlation between the LYC response of the subjects and their fasting plasma LYC concentration. Results showed that there was a positive relationship between these two variables (Pearson's r=0.37, P<0.05).

Genetic variants associated with the LYC response

As explained in the subjects and methods section, we used PLS regression to examine whether the 1885 candidate SNPs (used as qualitative X variables) could explain a significant part of the variability in the LYC response of the subjects. As shown in Table 2, the model including all SNPs explained the group variance with good accuracy (R 2 =0.95) but was not predictive of this variance (Q 2 =-0.1). Therefore, to improve the model and find an association of SNPs more predictive of the LYC response, we filtered out SNPs that made no important contribution, i.e. those who displayed the lowest variable importance in the projection (VIP) values. After applying several thresholds of VIP value (Table 2), we found that the best model obtained included 44 SNPs (28 not in linkage disequilibrium, plus 16 in linkage disequilibrium, shown in Supplementary table 3). The 28 SNPs were located in or near 16 genes (Table 3) and explained 72 % of the group variance, with a prediction index Q 2 of 56 % (Table 2). The robustness and the stability of the model were validated by three additional methods detailed in the Supplementary Methods section.

Using univariate statistics, the association of the 28 SNPs with the LYC response was further evaluated by comparing, for each SNP, the LYC response of subjects who bore different genotypes (Table 3). For 11 of the 28 SNPs, subjects who bore different genotypes exhibited a significantly different LYC response (q-value<0.05).

Genetic score to calculate the LYC response of a genotyped subject

Knowing a subject's genotype at the 28 aforementioned loci, it is possible to calculate his ability to respond to LYC, according to the following equation:

With RP as the responder phenotype (i.e. the LYC response), a as a constant, r i as the regression coefficient of the i th SNP included in the PLS regression model, and genotype.(SNP i ) as a Boolean variable indicating the subject's genotype at the i th SNP. A list of the regression coefficients calculated by the SIMCA software can be found in

Supplementary table 5.

Discussion

The first key observation of this study was the high interindividual variability observed in the LYC response to the test meal containing tomato puree. The 70% CV is in agreement with previous reports [START_REF] Diwadkar-Navsariwala | A physiological pharmacokinetic model describing the disposition of lycopene in healthy men[END_REF][START_REF] Stahl | Uptake of lycopene and its geometrical isomers is greater from heatprocessed than from unprocessed tomato juice in humans[END_REF][START_REF] Bowen | Variability of Serum Carotenoids in Reponse to Controlled Diets Containing Six Servings of Fruits and Vegetables per day[END_REF][START_REF] Johnson | Ingestion by men of a combined dose of beta-carotene and lycopene does not affect the absorption of beta-carotene but improves that of lycopene[END_REF][START_REF] O'neill | Intestinal absorption of -carotene, lycopene and lutein in men and women following a standard meal: response curves in the triacylglycerolrich lipoprotein fraction[END_REF][START_REF] Wang | Strong and weak plasma response to dietary carotenoids identified by cluster analysis and linked to beta-carotene 15,15'monooxygenase 1 single nucleotide polymorphisms[END_REF]. Until very recently, the reason for this high interindividual variability was not known. Only one study has attempted to link this variability with SNPs in two key genes of carotenoid metabolism, i.e. BCO1 and BCO2, by observing plasma LYC response following a 3 week supplementation with tomato or watermelon juice [START_REF] Wang | Strong and weak plasma response to dietary carotenoids identified by cluster analysis and linked to beta-carotene 15,15'monooxygenase 1 single nucleotide polymorphisms[END_REF]. This data suggested that subjects with the AA/CT genotype combination at rs12934922 and rs7501331 in BCO1 were more responsive to LYC than those without this genotype combination. However, numerous SNPs in genes related to other aspects of lycopene absorption and excretion likely impact LYC response. Indeed, we have recently shown that 73% of the interindividual variability in the bioavailability of the carotenoid lutein can be explained by a combination of 29 SNPs in genes involved in lutein and lipid metabolism [START_REF] Borel | Interindividual variability of lutein bioavailability in healthy men: characterization, genetic variants involved, and relation with fasting plasma lutein concentration[END_REF]. Moreover, LYC bioavailability, is likely affected by multiple parameters besides LYC absorptione.g. catabolism, tissue uptake, oxidation, etc. Therefore, we assessed the involvement of SNPs in all genes suspected to modulate this phenotype.

The result of the multivariate analysis, whose validity was verified by several tests, demonstrated that a significant part (72%) of the interindividual variability in the LYC response could be explained by 28 SNPs in or near 16 genes. Seven out of these 16 genes, i.e.

ABCA1, LPL, INSIG2, SLC27A6, LIPC, CD36

and APOB, have recently been found to be involved in the postprandial CM triacylglycerol response in the same group of subjects [START_REF] Desmarchelier | The postprandial chylomicron triacylglycerol response to dietary fat in healthy male adults is significantly explained by a combination of single nucleotide polymorphisms in genes involved in triacylglycerol metabolism[END_REF]. This was not surprising as most newly absorbed LYC is carried from the intestine to peripheral organs via CM, which are mainly composed of triacylglycerols. Since this study focuses on LYC bioavailability, we will only discuss the potential role of the 4 genes that were not associated with the CM triacylglycerol response and that had SNPs which displayed a significant corrected P-value (Table 3). These genes were ELOVL2 (ELOVL fatty acid elongase 2), MTTP (microsomal triglyceride transfer protein), ABCB1 (ATP-binding cassette, sub-family B, member 1) and SOD2 (superoxide dismutase 2, mitochondrial). First, it is striking to observe that 3 of the top 4 SNPs identified in the PLS model were related to ELOVL2. This result suggests that this gene plays a key role in the LYC response. ELOVL2 is known to catalyze the elongation of EPA (eicosapentaenoic acid) to DPA (docosapentaenoic acid) and DPA to DHA (docosahexaenoic acid). LYC is not considered to be a substrate for this enzyme, thus, this association is intriguing. Nevertheless, the fact that rs3798709 and rs9468304 in ELOVL2 were also associated with both the lutein [START_REF] Borel | Interindividual variability of lutein bioavailability in healthy men: characterization, genetic variants involved, and relation with fasting plasma lutein concentration[END_REF] and β-carotene response (data not shown submitted to publication) strongly supports its involvement in carotenoid metabolism. Three SNPs in MTTP were also found in the selected PLS model. MTTP encodes for the microsomal triglyceride transfer protein, which is involved in the packaging of triacylglycerols within the CM. Its association with the LYC response is therefore not surprising, as LYC is incorporated into CM in the enterocyte. ABCB1 encodes for the Pglycoprotein, an ATP-dependent drug efflux pump for xenobiotic compounds with broad substrate specificity. To the best of our knowledge, there is currently no study on the involvement of this protein in LYC transport, but the present association suggests that this protein may participate in LYC absorption, possibly by effluxing a fraction of uptaken LYC back to the intestinal lumen. The low absorption efficiency of LYC, about 30% at the dose of 10 mg [START_REF] Diwadkar-Navsariwala | A physiological pharmacokinetic model describing the disposition of lycopene in healthy men[END_REF], supports this hypothesis, but further studies are required to determine ABCA1 involvement. Our results also suggest that SOD2, responsible for converting superoxide byproducts to hydrogen peroxide and diatomic oxygen, is involved in LYC status, possibly through impacts on LYC metabolism. We hypothesize that when this enzyme is not efficient, superoxide by-products are quenched by LYC, leading to its degradation. Surprisingly, some genes assumed to be involved in intestinal LYC bioavailability and metabolism were absent from the selected PLS model. These genes are SCARB1 and CD36, who code for proteins involved in the cellular uptake of LYC [START_REF] Moussa | Lycopene absorption in human intestinal cells and in mice involves scavenger receptor class B type I but not Niemann-Pick C1-like 1[END_REF] [START_REF] Moussa | CD36 is involved in lycopene and lutein uptake by adipocytes and adipose tissue cultures[END_REF], and BCO2 [START_REF] Lindshield | Lycopenoids: are lycopene metabolites bioactive?[END_REF] and BCO1 [START_REF] Dela Sena | Substrate specificity of purified recombinant human beta-carotene 15,15'-oxygenase (BCO1)[END_REF], which have been shown in vitro to cleave LYC. The fact that SCARB1 was not associated with LYC bioavailability was surprising as this scavenger receptor has been involved in cellular uptake of LYC by intestinal cells [START_REF] Moussa | Lycopene absorption in human intestinal cells and in mice involves scavenger receptor class B type I but not Niemann-Pick C1-like 1[END_REF][START_REF] During | Carotenoid transport is decreased and expression of the lipid transporters SR-BI, NPC1L1, and ABCA1 is downregulated in Caco-2 cells treated with ezetimibe[END_REF] and a recent study showed that a SNP in this gene was associated with blood LYC concentration [START_REF] Zubair | Genetic variation predicts serum lycopene concentrations in a multiethnic population of postmenopausal women[END_REF]. The results with BCO1 are in contradiction with the work by Wang et al., cited earlier [START_REF] Wang | Strong and weak plasma response to dietary carotenoids identified by cluster analysis and linked to beta-carotene 15,15'monooxygenase 1 single nucleotide polymorphisms[END_REF] but match the findings for BCO2. We have three main hypotheses to explain these lacks of association. The first hypothesis is that SNPs genotyped in these genes do not result in a functionally different phenotype with regards to LYC bioavailability. The second hypothesis is that the association of SNPs in these genes is weaker than that of the SNPs in the selected model. In other words, these SNPs may play a minor role in LYC bioavailability. This is not in disagreement with the fact that they can play a significant role in fasting blood LYC concentrations. For example, SR-BI is expressed in several tissues which could explain that genetic variants in this gene play a key role in, for example, blood LYC uptake by other tissues while they do not play a key role in LYC uptake by the intestine.. Finally, the third hypothesis is that some SNPs in these genes were not entered in the PLS regression analysis because either they were not expressed on the BeadChips, or they were excluded from the analysis (for not following the Hardy-Weinberg equilibrium or because their genetic call rate was <95%). While we acknowledge these limitations of the study, the primary results remain, i.e. a significant fraction of the variability in LYC bioavailability is associated with a combination in genetic variants identified in our model.

After determining that LYC bioavailability is, at least partly, modulated by a combination of SNPs, the obvious question that arose was : "do these SNPs impacting LYC bioavailability affect long-term blood LYC status?" To answer this question, we assessed whether there was a relationship between the LYC response of the volunteers to the tomato puree test meal and their fasting plasma LYC concentrations. The result of this investigation, which showed a significant relationship between the two parameters, suggests that the ability to respond to dietary LYC is implicated in long term blood, and likely tissue, LYC concentrations. Nevertheless, the relatively low correlation coefficient, i.e. 0.37, supports the assumption that other factors, e.g. LYC catabolism, oxidative stress…, are involved in long term blood LYC concentrations.

To conclude, the results of this study demonstrate for the first time that interindividual variability in LYC bioavailability is, at least partly, genetically controlled. They also suggest that ELOVL2 is implicated in LYC, and more generally, carotenoid metabolism. Furthermore, the ability to respond to dietary LYC is a determinant of circulating fasting LYC concentrations. These associations will need to be validated in other populations, which will also allow for the identification of additional SNPs not included in our candidates based on the current knowledge of LYC metabolism, which is still quite limited. The ultimate objective of these studies will be to provide nutritionists with an accurate and validated genetic tool to predict one's individual LYC bioavailability for optimal LYC intake.

Tables Table 1. Characteristics of the subjects included in the statistical analysis of the results. Subjects were sorted by increasing postprandial CM LYC response (i.e., 0-8 h AUC).

Parameter

FiguresFigure 1 :

 1 Figures

Figure 2 :

 2 Figure 2: Individual AUCs of the postprandial CM LYC response after consumption of

Table 2 .

 2 Performances of different partial least squares regression models to explain the postprandial chylomicron lycopene response.1

	Mean 1 ± SEM

single nucleotide polymorphism; VIP, variable importance in the projection.

Table 3 .

 3 Genes and single nucleotide polymorphisms associated with the postprandial chylomicron lycopene response.1 SNPs present in the selected PLS regression model shown in Table2. SNPs are ranked by decreasing VIP value. Note that 16 out of the 44 SNPs present in the selected model were in linkage disequilibrium. Since these SNPs provided redundant information, we randomly kept one of each SNP (those presented in this table) in the final selected PLS model. The SNPs in linkage disequilibrium with some of these SNPs are shown in Supplemental

				Adjusted
	Gene and SNP rs no. 2	VIP value	SNP minor allele frequency
				P-value 3
	ELOVL2-rs3798709	3.38	0.252	0.030
	ELOVL2-rs9468304	3.33	0.302	0.030
	LPL-rs7005359	3.19	0.298	0.030
	ELOVL2-rs911196	3.07	0.252	0.030
	ABCA1-rs4149316	2.81	0.122	0.023
	MTTP-rs17029173	2.73	0.135	0.030
	ABCB1-rs10248420	2.67	0.347	0.030
	PKD1L2-rs935933	2.57	0.201	0.053
	MTTP-rs1032355	2.56	0.251	0.067
	ABCG2-rs1871744	2.55	0.173	0.061
	ABCA1-rs2791952	2.50	0.140	0.030
	LPL-rs7841189	2.44	0.148	0.063
	INSIG2-rs17006621	2.27	0.172	0.077
	ABCA1-rs3887137	2.15	0.123	0.076
	MTTP-rs745075	2.03	0.061	0.030
	NPC1L1-rs17725246	1.97	0.254	0.106
	LPL-rs17482753	1.95	0.088	0.101
	SOD2-rs9365046	1.93	0.169	0.039
	SLC27A6-rs10053477	1.91	0.209	0.090
	ABCA1-rs1331924	1.88	0.245	0.091
	ISX-rs2056983	1.85	0.117	0.092

1 2

table 2 .

 2

Student's t-test with the Benjamini-Hochberg correction was carried out to determine differences between the postprandial CM LYC response according to genotype groups for each SNP. SNP, single nucleotide polymorphism; rs, reference SNP; VIP, variable importance in the projection. A complete list of gene names and symbols can be found in Supplementary table 1.

Acknowledgements

We are very grateful to Dr. Rachel Kopec for critical comments on the manuscript.

The authors have no conflict of interest to declare.

The present work has received research funding from the European Community's Sixth Framework Programme. The funding was attributed to the Lycocard project (n°016213) which was an Integrated Project within the framework of the "Food Quality and Safety" programme. This publication reflects only the view of the authors. The Lycocard community is not liable for any use that may be made of the results.

//www.clinicaltrials.gov/ct2/. The ID number is NCT02100774.

Authors' contributions to manuscript:

PB designed research; MN conducted the clinical research; RB analysed lycopene by HPLC; CD and PB analyzed data and CD performed statistical analysis; PB and CD wrote the paper; PB and CD had primary responsibility for final content.