Food-related Differences in Human Metabolite Profiles

June 28, 2019 updated by: Imperial College London

Many population studies include food questionnaires (recording the normal food intake or the food intake of the study day). This is necessary, because diet is an important lifestyle factor, although food questionnaires are time-consuming and expensive. Moreover, mis-reporting is a very common problem. We therefore seek for a tool to validate food protocol.

The hypothesis is to find biochemical marker for animal protein, fruit intake and grape consumption in urinary metabolic profiles after specific food consumption. Furthermore we want to specify biomarkers for different animal protein sources, fish and beef.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

Volunteers are asked to follow a diet plan over the whole course of the study. Every newly introduced food (in this study the dinner on days 2-5) will cause a change in biochemical marker excretion with urine. To monitor the kinetics of biomarker excretion it is necessary to collect urine several times a day; we will ask volunteers to collect the first morning urine, before lunch, before dinner and before going to bed. Urine sampling will start with the first morning urine on day 1 and end with first morning urine on day 7.

As test food, we propose a fruit salad (apples, grapes, orange and grapefruit) on day 2, fish on day 3, grapes on day 4, beef on day 5 and again fish for lunch on day 6.

From day 0 (run-in day) to day 6 the basic diet will always be bread and cheese for breakfast, coffee in the morning, a ham sandwich for lunch, and pasta and tomato sauce for dinner. As beverages only water will be allowed (although wine is permitted on day 4 if the subject wishes but this is not a protocol requirement). The test foods will be consumed in addition to that.

All urine samples will then be analysed using high resolution NMR spectroscopy and mass spectrometry. Mathematical data analyses as well as the visual examinations of the NMR spectra will also be carried out to identify new food biomarkers.

Study Type

Interventional

Enrollment (Actual)

7

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • United Kingdom
      • London, United Kingdom, SW7 2AZ
        • Imperial College London

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 45 years (Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

Inclusion Criteria:

  • healthy individuals
  • male/female
  • aged 18-45 years
  • non-smoker
  • BMI 18-25 kg/m2

Exclusion Criteria:

  • regular drug intake
  • regular food supplements intake
  • antibiotics intake in the last 3 months
  • not willing to eat one or more items of the foods listed in the diet plan

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Basic Science
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: self-administered food intake
self-administered food intake according to dietary protocol
Dietary supplement: fish, beef, fruit

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
To elucidate urinary biochemical markers for the consumption of fish, beef, fruit salad and grape.
Time Frame: 12 months

1H NMR metabolic profiles will be acquired for all urine samples. These metabolic profiles contain a wealth of information about metabolites present in urine samples.

Multivariate mathematical model procedures, such as partial least squares discriminant analysis, will be employed to elucidate metabolic signatures associated to consumption of fish, beef, fruit salad and grape.
12 months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
To investigate the kinetics of elucidated biomarker excretion over time.
Time Frame: 12 months
Potential biomarkers (see primary outcome) will be quantified by integrating the NMR resonance and plotted over time.
12 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Imperial College London

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

June 1, 2009

Primary Completion (Actual)

December 1, 2009

Study Completion (Actual)

December 1, 2009

Study Registration Dates

First Submitted

April 7, 2010

First Submitted That Met QC Criteria

April 9, 2010

First Posted (Estimate)

April 12, 2010

Study Record Updates

Last Update Posted (Actual)

July 1, 2019

Last Update Submitted That Met QC Criteria

June 28, 2019

Last Verified

June 1, 2019

More Information

Terms related to this study

Other Study ID Numbers

  • 535-ICL-673

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Subscribe