Identification of New Biomarkers of Banana and Tomato Intake

NCT ID: NCT03581955

Last Updated: 2018-07-16

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 12 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2016-03-26
• Study Completion Date: 2016-06-16

Brief Summary

The intake of fruits and vegetables has been associated to a lower risk of developing metabolic diseases and cancer. The intake of tomato has been proposed to decrease the risk of prostate cancer while the high content of pro-vitamine A carotenes in banana have shown to alleviate Vitamin A deficiency in different countries. Interestingly in spite of their popularity, there are no biomarkers of banana intake reported in the literature while lycopene is the most frequently used metabolite to indicate tomato consumption however, its limited specificity and between-subjects variation sets doubt of its accuracy. Therefore, the identification of novel biomarkers for both banana and tomato is of great value. Untargeted metabolomics, allows a holistic analysis of the food metabolome allowing a deeper inquiry in the metabolism of different compounds and the recognition of patterns and individual differences that may lead to new hypothesis and further research. Therefore, the aim of the present study is to identify biomarkers of acute intake of banana and tomato using an untargeted approach on urine serum of 12 volunteers that participated in a crossover, randomized, controlled study. Volunteers consumed three different test foods: 1) 240g of banana, 2) 300g of tomato and 3) Fresubin 2kcal as control. Serum and urine samples were collected in kinetics over 24h and processed to be analyzed using LC-QTof analysis. The metabolomics profiles are compared using univariate (ANOVA) and multivariate statistical methods (PCA, PLSDA). The identification of discriminant compounds was performed by tandem mass fragmentation with a high-resolution LTQ-Orbitrab Mass spectrometer and by an extensive inquiry of different online databases.

Detailed Description

The rise of metabolomics along with different platforms such as liquid chromatography mass spectrometers (LC-MS) have allowed the assessment of thousands of metabolites simultaneously in biological samples and the recognition of patterns that may constitute a fingerprint of the intake of different foods. Recent studies demonstrated the great potential of metabolomics to discover new biomarkers of intake in intervention and cohort studies.The diversity of compounds found in food metabolomics represents a major challenge and so in an international effort to improve dietary biomarkers identification and validation, the Food Biomarkers Alliance (FOODBALL) has been created. In this project, 22 institutions from 11 different countries will collaborate in three main tasks: 1) Discovery of new dietary biomarker using a metabolomic approach, 2) systemic validation of existing and newly discovered biomarker to achieve a good coverage of food intake in different European populations and 3) exploring biological effects using biomarkers of intake (http://foodmetabolome.org/). With the latter, the necessity of building a chemical library that allows the use of standards for further identification arises. Along with FOODBALL, The Food Compound Exchange (FoodComEx) aims to improve the availability of analytical standards of biological compounds to achieve a better and easier biomarker identification (http://foodcomex.org/).

As part of INRA collaboration to FOODBALL and FoodComEx, the present project attempts to identify biomarkers of banana and tomato intake, through the exploration of the serum and urine metabolome of 12 subjects who consumed these foods following a randomized, controlled, crossover design. The present study was comprised of 3 different intervention periods and a minimum of 3 days washout between interventions. The intervention periods were comprised of 2 run in days, 1 intervention day and 1 post intervention day. In the first day of the run in period, subjects were instructed to avoid the intake of banana or tomato or any of their products; the day prior to the intervention volunteers were asked to avoid the intake of phytochemical rich foods and beverages such as wine, coffee, chocolate, tea, and other plant based foods including banana and tomato.In the morning of the intervention, day subjects arrived in fasting state to the research center at 7.30 am. Volunteers were randomly assigned to one of the three interventions, Fresubin ® 2kcal fiber, 240g of banana plus control drink, or 300g of tomato plus control drink plus 12g of refined sunflower oil. Throughout the intervention, subjects had free access to water, maximum 250ml of water per hour until 6 hours after the intake of the test food.

A trained phlebotomist placed a catheter on the subject's arm before the intake of the test foods to collect the baseline sample. Then four other samples were collected postprandially after 1h, 2h, 4h, and 6h. A total of 7 urine samples were collected. The first void of urine was collected by the subjects at home upon the morning of Day 3 and the rest of the samples after the intake of the test foods as follows: 0-1h, 1h-2h, 2h-4h, 4h-6h. The urine samples corresponding to 6h-12h and 12-24h interval were collected by volunteers at home until the morning after the intake of the food.

After the 6h collection of blood, the peripheral catheter was removed and subjects had lunch composed of white bread and cooked pasta, then subjects were allowed to go home. Before leaving the Investigation center, participants were instructed to prepare a standardized dinner based on pan fried chicken with butter and boiled rice with salt. Volunteers were not allowed to eat or drink anything except water and the standardized dinner.

On the morning of the post intervention day, subjects arrived in fasting state to the research center to give the 24h blood sample and deliver the 06-12h and 12-24h urine collection. Afterward, subjects were served breakfast at the research center and resumed their normal diet until the next run in days of the next intervention period.

Urine samples and serum samples were aliquoted and stored at -80° C until analysis.

Conditions

Biomarkers; Food Intake

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: CROSSOVER
• Primary Study Purpose: OTHER
• Blinding Strategy: NONE

Study Groups

Banana Cavendish

240g of fruit plus 150ml of Fresubin ® 2kcal fiber neutral flavor

Group Type: EXPERIMENTAL

Banana Cavendish

Intervention Type: OTHER

240g of fruit plus 150ml of control drink (Fresubin ® 2kcal fiber neutral flavor)

Control drink

250ml of Fresubin ® 2kcal fiber neutral flavor

Group Type: EXPERIMENTAL

Fresubin ® 2kcal fiber neutral flavor

Intervention Type: OTHER

250 ml Fresubin ® 2kcal fiber neutral flavor

Tomato

300g of tomato plus of Fresubin ® 2kcal fiber neutral flavor plus 12g of refined sunflower oil.

Group Type: EXPERIMENTAL

Tomato

Intervention Type: OTHER

300g of raw tomato ("coeur de boeuf") with refined sunflower oil (12g) and 150ml of control drink (Fresubin ® 2kcal fiber neutral flavor).

Interventions

Banana Cavendish

240g of fruit plus 150ml of control drink (Fresubin ® 2kcal fiber neutral flavor)

Intervention Type: OTHER

Tomato

300g of raw tomato ("coeur de boeuf") with refined sunflower oil (12g) and 150ml of control drink (Fresubin ® 2kcal fiber neutral flavor).

Intervention Type: OTHER

Fresubin ® 2kcal fiber neutral flavor

250 ml Fresubin ® 2kcal fiber neutral flavor

Intervention Type: OTHER

Other Intervention Names

Test Food; Test Food; Control

Eligibility Criteria

Inclusion Criteria

• Healthy males and females
• Aged 18- 40 years
• BMI >18.5 and < 30 kg/m2
• Willing/able to consume all test foods (tomato, banana, Fresubin drink) and the standardized meals (rice and chicken)

Exclusion Criteria

• Smokers
• Diagnosed health condition (chronic or infectious disease)
• Taking nutritional supplements (e.g. vitamins, minerals) several times a week.
• Taking medication (oral contraceptive pill is allowed).
• Pregnant, lactating.
• Antibiotics treatment within 3 months prior to intervention.
• Vegetarians, as standardized meals will contain meat.
• Not willing to follow nutritional restrictions, including drinking alcohol during study days
• Not willing/able to give informed consent or to sign informed consent.
• Not affiliated to National Health Insurance.
• Being in exclusion on the National Volunteers Data file or refusing to be registered on the National Volunteers Data file.
• Currently participating or who having got 4500€ in this year to have participated in another clinical trial.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 40 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

National Research Agency, France

OTHER

Sponsor Role: collaborator

Claudine MANACH

OTHER

Sponsor Role: lead

Responsible Party

Claudine MANACH

Principal Investigator

Responsibility Role: SPONSOR_INVESTIGATOR

Principal Investigators

Claudine Manach, Researcher

Role: PRINCIPAL_INVESTIGATOR

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

Locations

INRA

Clermont-Ferrand, Rhône-Alpes-Auvergne, France

Countries

France

References

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Reference Type: BACKGROUND

PMID: 24390407 (View on PubMed)

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Reference Type: BACKGROUND

PMID: 19764066 (View on PubMed)

Scalbert A, Brennan L, Manach C, Andres-Lacueva C, Dragsted LO, Draper J, Rappaport SM, van der Hooft JJ, Wishart DS. The food metabolome: a window over dietary exposure. Am J Clin Nutr. 2014 Jun;99(6):1286-308. doi: 10.3945/ajcn.113.076133. Epub 2014 Apr 23.

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Reference Type: BACKGROUND

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Reference Type: BACKGROUND

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Reference Type: BACKGROUND

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Reference Type: BACKGROUND

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Reference Type: BACKGROUND

Manach C., Brennan L, Drasgted L.O. Metabolomics to evaluate food intake and utilization in nutritional epidemiology. In: Metabolomics as a Tool in Nutritional Research, Woodhead publishing 2015. pp.167-196

Reference Type: BACKGROUND

Kesse-Guyot E, Castetbon K, Touvier M, Hercberg S, Galan P. Relative validity and reproducibility of a food frequency questionnaire designed for French adults. Ann Nutr Metab. 2010;57(3-4):153-62. doi: 10.1159/000321680. Epub 2010 Nov 16.

Reference Type: BACKGROUND

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Vazquez-Manjarrez N, Weinert CH, Ulaszewska MM, Mack CI, Micheau P, Petera M, Durand S, Pujos-Guillot E, Egert B, Mattivi F, Bub A, Dragsted LO, Kulling SE, Manach C. Discovery and Validation of Banana Intake Biomarkers Using Untargeted Metabolomics in Human Intervention and Cross-sectional Studies. J Nutr. 2019 Oct 1;149(10):1701-1713. doi: 10.1093/jn/nxz125.

Reference Type: DERIVED

PMID: 31240312 (View on PubMed)

Provided Documents

Document Type: Study Protocol

View Document

Document Type: Statistical Analysis Plan

View Document

Other Identifiers

2016-A00153-48

Identifier Type: -

Identifier Source: org_study_id