Identification of New Biomarkers of Banana and Tomato Intake

NCT03581955 | Completed

• 1 other identifier: 2016-A00153-48
• Study Type: interventional
• Target: 12
• Locations: 1 country
• Sites: 1

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.

Conditions

Biomarkers; Food Intake

Keywords

biomarkers; diet; banana; tomato; urine; plasma; intake; exposure; metabolomics

Outcome Measures

Primary Outcomes (1)

• Changes in metabolite profiles present in blood serum and urine before the dietary intervention (t=0) and in kinetics over 24 hours.

  Metabolite profiles analyzed using a non-targeted metabolomics approach with a UPLC-MS platform. Blood serum samples collected at time 0, 1 hour, 2 hours, 4 hours, 6 hours and 24 hours. Urine fractions collected at 0-1 hours, 1-2 hours, 2-4 hours, 4-6 hours, 6-12 hours, 12-24 hours. Identification of biomarkers of acute intake of the foods of interest through the comparison of metabolomes after either single dose of tomato, banana or control drink.

  0-24 hours

Secondary Outcomes (1)

• Collection of pools of urine and serum samples after acute intake of tomato or banana to be used as analytical standards or for the identification of specific metabolites of banana or tomato components.

  0-24 hours

Study Arms (3)

Banana Cavendish

EXPERIMENTAL

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

Other: Banana Cavendish

Control drink

EXPERIMENTAL

250ml of Fresubin ® 2kcal fiber neutral flavor

Other: Fresubin ® 2kcal fiber neutral flavor

Tomato

EXPERIMENTAL

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

Other: Tomato

Interventions

Banana Cavendish OTHER

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

Also known as: Test Food

Banana Cavendish

Tomato OTHER

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

Also known as: Test Food

Tomato

Fresubin ® 2kcal fiber neutral flavor OTHER

250 ml Fresubin ® 2kcal fiber neutral flavor

Also known as: Control

Control drink

Eligibility Criteria

• Age: 18 Years - 40 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)

You may qualify if:

• 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)

You may not qualify if:

• 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.
• Currently participating or who having got 4500€ in this year to have participated in another clinical trial.

Sponsors & Collaborators

• Claudine MANACH: lead
• National Research Agency, France: collaborator

Study Sites (1)

INRA

Clermont-Ferrand, Rhône-Alpes-Auvergne, 63122, France

Location

Related Publications (11)

• Andersen MB, Kristensen M, Manach C, Pujos-Guillot E, Poulsen SK, Larsen TM, Astrup A, Dragsted L. Discovery and validation of urinary exposure markers for different plant foods by untargeted metabolomics. Anal Bioanal Chem. 2014 Mar;406(7):1829-44. doi: 10.1007/s00216-013-7498-5. Epub 2014 Jan 4.

  PMID: 24390407 BACKGROUND

• Manach C, Hubert J, Llorach R, Scalbert A. The complex links between dietary phytochemicals and human health deciphered by metabolomics. Mol Nutr Food Res. 2009 Oct;53(10):1303-15. doi: 10.1002/mnfr.200800516.

  PMID: 19764066 BACKGROUND

• 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.

  PMID: 24760973 BACKGROUND

• Re R, Bramley PM, Rice-Evans C. Effects of food processing on flavonoids and lycopene status in a Mediterranean tomato variety. Free Radic Res. 2002 Jul;36(7):803-10. doi: 10.1080/10715760290032584.

  PMID: 12180131 BACKGROUND

• Giovannucci E. Tomatoes, tomato-based products, lycopene, and cancer: review of the epidemiologic literature. J Natl Cancer Inst. 1999 Feb 17;91(4):317-31. doi: 10.1093/jnci/91.4.317.

  PMID: 10050865 BACKGROUND

• Pereira A, Maraschin M. Banana (Musa spp) from peel to pulp: ethnopharmacology, source of bioactive compounds and its relevance for human health. J Ethnopharmacol. 2015 Feb 3;160:149-63. doi: 10.1016/j.jep.2014.11.008. Epub 2014 Nov 13.

  PMID: 25449450 BACKGROUND

• Pujos-Guillot E, Hubert J, Martin JF, Lyan B, Quintana M, Claude S, Chabanas B, Rothwell JA, Bennetau-Pelissero C, Scalbert A, Comte B, Hercberg S, Morand C, Galan P, Manach C. Mass spectrometry-based metabolomics for the discovery of biomarkers of fruit and vegetable intake: citrus fruit as a case study. J Proteome Res. 2013 Apr 5;12(4):1645-59. doi: 10.1021/pr300997c. Epub 2013 Mar 5.

  PMID: 23425595 BACKGROUND

• Peralta I, Spooner DM. Genetic Improvement of Solanaceous Crops Volume 2: Tomato. CRC Press; 2006. https://books.google.com/books?hl=en&lr=&id=1m7RBQAAQBAJ&pgis=1. Accessed December 18, 2015

  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

  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.

  PMID: 21079389 BACKGROUND

• 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.

  PMID: 31240312 DERIVED

MeSH Terms

Interventions

Fresubin

Study Officials

• Claudine Manach, Researcher

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

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: OTHER
• Intervention Model: CROSSOVER
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Principal Investigator

Model Details: The present project is a randomized, controlled, crossover study with 12 subjects. A cross-over design has been selected as each subject can serve as his/her own control thereby minimizing variations. The intervention order was randomized. The study design does not allow blinding as intervention is the ingestion of different foods.In this study, we assessed the metabolomic profiles of human biofluids after consumption of two different foods: banana (240g peeled fruit) and tomato (300g fresh fruit) in order to identify novel biomarkers for each food. As a control diet, a high energy high protein drink, Fresubin ® 2kcal fiber (Fresinius kabi) was used. The study comprised three dietary interventions of 4 days each and a wash-out period no shorter than 3 days.

Study Record Dates

• First Submitted: August 31, 2017
• First Posted: July 10, 2018
• Study Start: March 26, 2016
• Primary Completion: May 19, 2016
• Study Completion: June 16, 2016
• Last Updated: July 16, 2018

Record last verified: 2018-07

Data Sharing

• IPD Sharing: Will not share

Locations

FR (1)