Nutrition, HealthyBIAMEXNCT06449170
Discovery of Biomarkers of Intake of of Highly Consumed Foods in Mexico
A study testing Mango Ataulfo, Avocado Hass and Nopal in people with Nutrition, Healthy and Diet Habit, run by Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran at 1 site in Mexico.
Trial summary
To determine diet-health associations, researchers rely on information obtained from dietary instruments, such as the 24-hour recall (R24H), food frequency questionnaires (FFQ) and food diaries, in clinical studies. Read more about this study
- Who is it for?
- Ages 18 to 40 yearsHealthy volunteers can take part
- Conditions the study is for
- Nutrition, Healthy, Diet Habit, Diet, Healthy
- What is being tested?
- Mango Ataulfo, Avocado Hass and Nopal
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 12 participants
- Where
- 1 siteMexico
- Study dates
- 1 Jan 2023to 31 Dec 2024
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 40 years
- All sexes
- Healthy volunteers accepted
- Adult
Who may be able to join
- Signed informed consent
- Healthy males and females
- BMI >18.5 and < 25 kg/m2
- Willing/able to consume all test foods and the standardized meals
Who cannot join
- Smokers
- Diagnosed health condition (chronic or infectious disease)
- Taking nutritional supplements (e.g. vitamins, minerals) several times a week.
- Taking medication.
- Pregnant, lactating.
- Antibiotics treatment within 3 months prior to intervention.
Show all 9Show fewer
- Vegetarians, as standardized meals will contain meat.
- Not willing to follow nutritional restrictions, including drinking alcohol during study days
- Allergic to foods of interest
Trial locations and contacts
1 site in 1 country.
Mexico1 site
Instituto de Ciencias Médicas y Nutrición Salvador Zubirán
Mexico City, 14080
About this study
Official title: BIAMEX: Discovery of Biomarkers of Intake of Highly Consumed Foods in Mexico by Untargeted Metabolomics
To determine diet-health associations, researchers rely on information obtained from dietary instruments, such as the 24-hour recall (R24H), food frequency questionnaires (FFQ) and food diaries, in clinical studies. However, it is widely recognized that the information provided by the different instruments is biased by different factors including recall errors and respondent burden. The impact of the variability produced by this bias decreases the robustness of diet-health associations which results in the creation of less efficient standards and recommendations for our population. To address this, the discovery of biomarkers of food intake (BFIs) is an objective tool that indicates exposure to specific foods or various dietary patterns. BFIs allow the calibration of dietary information to obtain the real consumption of the individual and thus clarify the relationship between different pathologies of interest and the intake of different foods. BIAMEX will initially focus on the discovery of BFIs of nopal, corn tortilla, mango, avocado, guava and amaranth. For this purpose, a controlled crossover intervention study is being carried out with the 6 foods to be investigated where 24h urine and plasma samples are being collected. Subsequently, the samples collected will be analyzed by mass spectrometry.
Read the detailed description
The BIAMEX study aims to address the challenge of improving the accuracy of dietary assessment, a critical factor in misunderstanding the relationship between diet and disease. Traditional dietary assessment tools, such as 24-hour recalls and food frequency questionnaires, are susceptible to biases related to their retrospective nature, such as memory errors and respondent burden. To overcome these limitations, BIAMEX focuses on discovering biomarkers on food intake (BFIs) for foods that originate in our country and are highly consumed by the population. This project will investigate the BFIs for nopal, corn tortilla, mango, avocado, guava, and amaranth.
This exploratory study employs a randomized, open, crossover, controlled design to investigate the metabolomic changes in urine and serum samples from healthy volunteers following the consumption of the selected foods. The interventions aim to assess the impact of each food intake on the metabolomic profile of the participants using an untargeted approach with liquid chromatography-mass spectrometry.
Participants were briefed at the Instituto Nacional de Ciencias Médicas y Nutrición "Salvador Zubirán" on the study's aims, procedures, and benefits before providing informed consent. Subsequent steps included clinical history documentation and blood sampling for eligibility assessment, focusing on fasting glucose, cholesterol levels, and other health indicators. Volunteers underwent seven distinct food interventions in a randomized manner, including mango, avocado, nopal, corn tortillas, guavas, amaranth, and Supportan® drink Cappuccino as the control. This beverage was chosen to avoid metabolomic overlap with the different foods, ensuring distinct biomarker detection. Preceding the intervention days, subjects followed a low-polyphenol diet, excluding test foods and phytochemicals-rich items such as tea, coffee, or chocolate, culminating in a standardized dinner. On the intervention day, subjects arrived fasting at the institution and provided a baseline serum and urine samples. Then, subjects were provided with the test food, after which urine and serum samples were collected at 1h, 2h,4h, 6h postprandially on site. After the six-hour timepoint, the catheter was removed, and a standardized lunch was provided. Subjects continued to collect urine samples at home, corresponding to the 12h and 24h urine collection, using materials provided by the investigation team. Additionally, subjects received dietary instructions and menus to follow for the rest of the day. On the day after the intervention, subjects returned to the institution to deliver the urine collections and to provide the last serum sample corresponding to the 24-hour timepoint. Once the sample was collected, subjects were provided with a complimentary breakfast, and their habitual diet was resumed. This experimental procedure was repeated for each food separated by a 7-day wash-out period.
- Conditions
- Nutrition, Healthy, Diet Habit, Diet, Healthy, Dietary Exposure
- Being tested
- Mango Ataulfo, Avocado Hass, Nopal, 3 corn tortilla, Guava
- Keywords
- metabolomics, nutrition, dietary biomarkers, dietary exposure
- Medical subject headings
- Feeding Behavior
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Mango AtaulfoOther
In this intervention, subjects consumed 150g of mango Ataulfo plus 150 ml of control beverage (Supportan® Drink Cappuccino). The addition of the control beverage has the purpose of providing energy intake and limiting the noise that the control beverage may contribute to the metabolomic profile in urine and serum.
Avocado HassOther
In this intervention, subjects consumed 120g of avocado hass plus 150 ml of a control beverage (Supportan® Drink Cappuccino). The addition of the control beverage provides energy intake and limits the noise that the beverage may contribute to the metabolomic profile in urine and serum.
NopalOther
In this intervention, subjects consumed 300g of cooked nopal and 150 ml of control beverage (Supportan® Drink Cappuccino). The addition of the control beverage provides energy intake and limits the noise that the beverage may contribute to the metabolic profile in urine and serum.
3 corn tortillaOther
In this intervention, subjects consumed 3 corn tortillas and 150 ml of control beverage (Supportan® Drink Cappuccino). The addition of the control beverage provides energy intake and limits the noise that the beverage may contribute to the metabolic profile in urine and serum.
GuavaOther
In this intervention, subjects consumed 3 guavas and 150 ml of control beverage (Supportan® Drink Cappuccino). The addition of the control beverage provides energy intake and limits the noise that the beverage may contribute to the metabolic profile in urine and serum.
AmaranthOther
In this intervention, subjects consumed 1/2 cup of amaranth and 150 ml of control beverage (Supportan® Drink Cappuccino). The addition of the control beverage provides energy intake and limits the noise that the beverage may contribute to the metabolic profile in urine and serum.
Control Beverage (Supportan Drink ® Capuccino)Dietary supplement
In this intervention, subjects consumed 290ml of Supportan Drink ® Capuccino to act as a control for the metabolomic profiling in urine and serum.
| Study group | Role | What they receive |
|---|---|---|
| Mango Ataulfo | Other | 150g of mango Ataulfo plus 150 ml of control beverage (Supportan® Drink Cappuccino) plus 15ml of sunflower seed oil Receives: Other: Mango Ataulfo |
| Avocado Hass | Other | 120g of avocado hass plus 150ml of control beverage (Supportan® Drink Cappuccino) Receives: Other: Avocado Hass |
| Boiled Nopal | Other | 300g of boiled nopal plus 150 ml of control beverage (Supportan® Drink Cappuccino) plus 18ml of sunflower seed oil Receives: Other: Nopal |
| Corn Tortilla | Other | 3 pieces of corn tortilla plus 150 ml of control beverage (Supportan® Drink Cappuccino) plus 2ml of sunflower seed oil Receives: Other: 3 corn tortilla |
| Guava | Other | 3 pieces of guava plus 150 ml of control beverage (Supportan® Drink Cappuccino) plus 16ml of sunflower seed oil Receives: Other: Guava |
| Amaranth | Other | 1/2 cup of amaranth plus 150 ml of control beverage (Supportan® Drink Cappuccino) plus 35ml of sunflower seed oil Receives: Other: Amaranth |
| Supportan® DKN Cappuccino | Other | 290ml of control beverage (Supportan® Drink Cappuccino) Receives: Dietary Supplement: Control Beverage (Supportan Drink ® Capuccino) |
What is being measured
The primary outcome is the main question the study is designed to answer.
Metabolic profiling of urine samples after intake of mango, amaranth, nopal, corn tortilla, avocado, and guava, detected as mass-to-charge signals (cps) by an untargeted metabolomics approach over 24 hours post-intake.
Given the absence of a priori knowledge of specific urinary biomarkers of intake for mango, nopal, amaranth, avocado, corn tortilla, and guava, an untargeted metabolomics approach will be employed to identify them. As an exploratory approach, this methodology will determine the myriad of signals (mass-to-charge ratios) present in urine samples, which correspond to metabolites that become bioavailable after the intake of the test foods, collected at 0-1, 1-2, 4-6, 6-12, and 12-24 hours after intake. The analysis of the patterns in the metabolome will facilitate the discovery of potential biomarkers of intake.
Measured: Before intake of foods 00 hours to 24 hours after intake.
Metabolic profiling of serum samples after intake of mango, amaranth, nopal, corn tortilla, avocado, and guava, detected as mass-to-charge signals (cps) by an untargeted metabolomics approach over 24 hours post-intake.
Given the absence of a priori knowledge of specific serum biomarkers of intake for mango, nopal, amaranth, avocado, corn tortilla, and guava, an untargeted metabolomics approach will be employed to identify them. As an exploratory approach, this methodology will determine the myriad of signals (mass-to-charge ratios) present in serum samples collected at baseline, 1 hour, 2 hours, 4 hours, 6 hours, and 24 hours after the intake of. The analysis of the patterns in the metabolome will facilitate the discovery of potential biomarkers of intake.
Measured: Before intake of foods 00 hours to 24 hours after intake.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Jun 2024
- Study start1 Jan 2023
- Primary completion5 Apr 2024
- Study completion31 Dec 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (27)Papers the sponsor has linked to this study.
- Other trials for Nutrition, HealthyStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Basic science
- Allocation
- Randomised
- Intervention model
- Crossover
- Model description
- This is a randomized, open, crossover, and controlled design study. A total of 12 healthy subjects (six males and six females) aged 18-40 years with a BMI of 18.5-24.9 kg/m\^2 were recruited. Participants underwent seven interventions (each featuring one of the selected foods or a control beverage), with a washout period of 7 days between interventions. Each intervention is as follows: 150g of mango + 150ml of control beverage, 120g of avocado + 150ml of control beverage, 300g of cooked nopal + 150ml of control beverage, 3 corn tortillas + 150ml of control beverage, 3 guavas + 150ml of control beverage, ½ cup of amaranth + 150ml of control beverage, 290ml of control beverage
- Masking
- None (open label)
- Enrolment
- 12 participants (actual)
Sponsor and investigators
- Lead sponsor
- Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Natalia Vázquez Manjarrez, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran
- Investigators
- Natalia Vázquez Manjarrez, PhD, Principal investigator, National Institute of Medical Sciences and Nutrition Salvador Zubirán
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06449170
- Sponsor's protocol ID
- 4044
- Acronym
- BIAMEX
- Status last verified
- Jun 2024
- First submitted
- 22 May 2024
- Last updated
- 7 Jun 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Archer E, Marlow ML, Lavie CJ. Controversy and debate: Memory-Based Methods Paper 1: the fatal flaws of food frequency questionnaires and other memory-based dietary assessment methods. J Clin Epidemiol. 2018 Dec;104:113-124. doi: 10.1016/j.jclinepi.2018.08.003. Epub 2018 Aug 17.
PubMed 30121379Tinker LF, Sarto GE, Howard BV, Huang Y, Neuhouser ML, Mossavar-Rahmani Y, Beasley JM, Margolis KL, Eaton CB, Phillips LS, Prentice RL. Biomarker-calibrated dietary energy and protein intake associations with diabetes risk among postmenopausal women from the Women's Health Initiative. Am J Clin Nutr. 2011 Dec;94(6):1600-6. doi: 10.3945/ajcn.111.018648. Epub 2011 Nov 9.
PubMed 22071707Vanderslice JT, Higgs DJ. Vitamin C content of foods: sample variability. Am J Clin Nutr. 1991 Dec;54(6 Suppl):1323S-1327S. doi: 10.1093/ajcn/54.6.1323s.
PubMed 1962591Andersen 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.
PubMed 24390407Gibbons H, Michielsen CJR, Rundle M, Frost G, McNulty BA, Nugent AP, Walton J, Flynn A, Gibney MJ, Brennan L. Demonstration of the utility of biomarkers for dietary intake assessment; proline betaine as an example. Mol Nutr Food Res. 2017 Oct;61(10). doi: 10.1002/mnfr.201700037. Epub 2017 Jul 20.
PubMed 28556565Cuparencu C, Rinnan A, Dragsted LO. Combined Markers to Assess Meat Intake-Human Metabolomic Studies of Discovery and Validation. Mol Nutr Food Res. 2019 Sep;63(17):e1900106. doi: 10.1002/mnfr.201900106. Epub 2019 Jun 13.
PubMed 31141834Vazquez-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.
PubMed 31240312Giesbertz P, Brandl B, Lee YM, Hauner H, Daniel H, Skurk T. Specificity, Dose Dependency, and Kinetics of Markers of Chicken and Beef Intake Using Targeted Quantitative LC-MS/MS: A Human Intervention Trial. Mol Nutr Food Res. 2020 Mar;64(5):e1900921. doi: 10.1002/mnfr.201900921. Epub 2020 Jan 29.
PubMed 31916678Ulaszewska MM, Weinert CH, Trimigno A, Portmann R, Andres Lacueva C, Badertscher R, Brennan L, Brunius C, Bub A, Capozzi F, Cialie Rosso M, Cordero CE, Daniel H, Durand S, Egert B, Ferrario PG, Feskens EJM, Franceschi P, Garcia-Aloy M, Giacomoni F, Giesbertz P, Gonzalez-Dominguez R, Hanhineva K, Hemeryck LY, Kopka J, Kulling SE, Llorach R, Manach C, Mattivi F, Migne C, Munger LH, Ott B, Picone G, Pimentel G, Pujos-Guillot E, Riccadonna S, Rist MJ, Rombouts C, Rubert J, Skurk T, Sri Harsha PSC, Van Meulebroek L, Vanhaecke L, Vazquez-Fresno R, Wishart D, Vergeres G. Nutrimetabolomics: An Integrative Action for Metabolomic Analyses in Human Nutritional Studies. Mol Nutr Food Res. 2019 Jan;63(1):e1800384. doi: 10.1002/mnfr.201800384. Epub 2018 Oct 11.
PubMed 30176196Dragsted LO, Gao Q, Scalbert A, Vergeres G, Kolehmainen M, Manach C, Brennan L, Afman LA, Wishart DS, Andres Lacueva C, Garcia-Aloy M, Verhagen H, Feskens EJM, Pratico G. Validation of biomarkers of food intake-critical assessment of candidate biomarkers. Genes Nutr. 2018 May 30;13:14. doi: 10.1186/s12263-018-0603-9. eCollection 2018.
PubMed 29861790Barnes RC, Krenek KA, Meibohm B, Mertens-Talcott SU, Talcott ST. Urinary metabolites from mango (Mangifera indica L. cv. Keitt) galloyl derivatives and in vitro hydrolysis of gallotannins in physiological conditions. Mol Nutr Food Res. 2016 Mar;60(3):542-50. doi: 10.1002/mnfr.201500706. Epub 2016 Feb 2.
PubMed 26640139Kim H, Castellon-Chicas MJ, Arbizu S, Talcott ST, Drury NL, Smith S, Mertens-Talcott SU. Mango (Mangifera indica L.) Polyphenols: Anti-Inflammatory Intestinal Microbial Health Benefits, and Associated Mechanisms of Actions. Molecules. 2021 May 6;26(9):2732. doi: 10.3390/molecules26092732.
PubMed 34066494Ferreira CM, Vieira AT, Vinolo MA, Oliveira FA, Curi R, Martins Fdos S. The central role of the gut microbiota in chronic inflammatory diseases. J Immunol Res. 2014;2014:689492. doi: 10.1155/2014/689492. Epub 2014 Sep 18.
PubMed 25309932Dreher ML, Davenport AJ. Hass avocado composition and potential health effects. Crit Rev Food Sci Nutr. 2013;53(7):738-50. doi: 10.1080/10408398.2011.556759.
PubMed 23638933Fulgoni VL 3rd, Dreher M, Davenport AJ. Avocado consumption is associated with better diet quality and nutrient intake, and lower metabolic syndrome risk in US adults: results from the National Health and Nutrition Examination Survey (NHANES) 2001-2008. Nutr J. 2013 Jan 2;12:1. doi: 10.1186/1475-2891-12-1.
PubMed 23282226
Study at a glance
From the registry record, last updated by the sponsor on 7 Jun 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- BIAMEX: Discovery of Biomarkers of Intake of Highly Consumed Foods in Mexico by Untargeted Metabolomics
- ClinicalTrials.gov ID
- NCT06449170
- Acronym / sponsor ID
- BIAMEX / 4044
- Conditions
- Nutrition, Healthy, Diet Habit, Diet, Healthy, Dietary Exposure
- Keywords
- metabolomics, nutrition, dietary biomarkers, dietary exposure
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 12 participants (actual)
- Lead sponsor
- Instituto Nacional de Ciencias Medicas y Nutricion Salvador ZubiranUniversity, hospital or other
- Study start
- 1 Jan 2023 (actual)
- Primary completion
- 5 Apr 2024 (actual)
- Study completion
- 31 Dec 2024 (estimated)
- First posted
- 7 Jun 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
To determine diet-health associations, researchers rely on information obtained from dietary instruments, such as the 24-hour recall (R24H), food frequency questionnaires (FFQ) and food diaries, in clinical studies. However, it is widely recognized that the information provided by the different instruments is biased by different factors including recall errors and respondent burden. The impact of the variability produced by this bias decreases the robustness of diet-health associations which results in the creation of less efficient standards and recommendations for our population. To address this, the discovery of biomarkers of food intake (BFIs) is an objective tool that indicates exposure to specific foods or various dietary patterns. BFIs allow the calibration of dietary information to obtain the real consumption of the individual and thus clarify the relationship between different pathologies of interest and the intake of different foods. BIAMEX will initially focus on the discovery of BFIs of nopal, corn tortilla, mango, avocado, guava and amaranth. For this purpose, a controlled crossover intervention study is being carried out with the 6 foods to be investigated where 24h urine and plasma samples are being collected. Subsequently, the samples collected will be analyzed by mass spectrometry.
Detailed description
The BIAMEX study aims to address the challenge of improving the accuracy of dietary assessment, a critical factor in misunderstanding the relationship between diet and disease. Traditional dietary assessment tools, such as 24-hour recalls and food frequency questionnaires, are susceptible to biases related to their retrospective nature, such as memory errors and respondent burden. To overcome these limitations, BIAMEX focuses on discovering biomarkers on food intake (BFIs) for foods that originate in our country and are highly consumed by the population. This project will investigate the BFIs for nopal, corn tortilla, mango, avocado, guava, and amaranth.
This exploratory study employs a randomized, open, crossover, controlled design to investigate the metabolomic changes in urine and serum samples from healthy volunteers following the consumption of the selected foods. The interventions aim to assess the impact of each food intake on the metabolomic profile of the participants using an untargeted approach with liquid chromatography-mass spectrometry.
Participants were briefed at the Instituto Nacional de Ciencias Médicas y Nutrición "Salvador Zubirán" on the study's aims, procedures, and benefits before providing informed consent. Subsequent steps included clinical history documentation and blood sampling for eligibility assessment, focusing on fasting glucose, cholesterol levels, and other health indicators. Volunteers underwent seven distinct food interventions in a randomized manner, including mango, avocado, nopal, corn tortillas, guavas, amaranth, and Supportan® drink Cappuccino as the control. This beverage was chosen to avoid metabolomic overlap with the different foods, ensuring distinct biomarker detection. Preceding the intervention days, subjects followed a low-polyphenol diet, excluding test foods and phytochemicals-rich items such as tea, coffee, or chocolate, culminating in a standardized dinner. On the intervention day, subjects arrived fasting at the institution and provided a baseline serum and urine samples. Then, subjects were provided with the test food, after which urine and serum samples were collected at 1h, 2h,4h, 6h postprandially on site. After the six-hour timepoint, the catheter was removed, and a standardized lunch was provided. Subjects continued to collect urine samples at home, corresponding to the 12h and 24h urine collection, using materials provided by the investigation team. Additionally, subjects received dietary instructions and menus to follow for the rest of the day. On the day after the intervention, subjects returned to the institution to deliver the urine collections and to provide the last serum sample corresponding to the 24-hour timepoint. Once the sample was collected, subjects were provided with a complimentary breakfast, and their habitual diet was resumed. This experimental procedure was repeated for each food separated by a 7-day wash-out period.
Study design
- Primary purpose
- Basic science
- Allocation
- Randomised
- Intervention model
- Crossover
- Masking
- None (open label)
- Number of arms
- 7
- Model description
- This is a randomized, open, crossover, and controlled design study. A total of 12 healthy subjects (six males and six females) aged 18-40 years with a BMI of 18.5-24.9 kg/m^2 were recruited. Participants underwent seven interventions (each featuring one of the selected foods or a control beverage), with a washout period of 7 days between interventions. Each intervention is as follows: 150g of mango + 150ml of control beverage, 120g of avocado + 150ml of control beverage, 300g of cooked nopal + 150ml of control beverage, 3 corn tortillas + 150ml of control beverage, 3 guavas + 150ml of control beverage, ½ cup of amaranth + 150ml of control beverage, 290ml of control beverage
| Arm | Type | Receives |
|---|---|---|
| Mango Ataulfo | Other | Other: Mango Ataulfo150g of mango Ataulfo plus 150 ml of control beverage (Supportan® Drink Cappuccino) plus 15ml of sunflower seed oil |
| Avocado Hass | Other | Other: Avocado Hass120g of avocado hass plus 150ml of control beverage (Supportan® Drink Cappuccino) |
| Boiled Nopal | Other | Other: Nopal300g of boiled nopal plus 150 ml of control beverage (Supportan® Drink Cappuccino) plus 18ml of sunflower seed oil |
| Corn Tortilla | Other | Other: 3 corn tortilla3 pieces of corn tortilla plus 150 ml of control beverage (Supportan® Drink Cappuccino) plus 2ml of sunflower seed oil |
| Guava | Other | Other: Guava3 pieces of guava plus 150 ml of control beverage (Supportan® Drink Cappuccino) plus 16ml of sunflower seed oil |
| Amaranth | Other | Other: Amaranth1/2 cup of amaranth plus 150 ml of control beverage (Supportan® Drink Cappuccino) plus 35ml of sunflower seed oil |
| Supportan® DKN Cappuccino | Other | Dietary Supplement: Control Beverage (Supportan Drink ® Capuccino)290ml of control beverage (Supportan® Drink Cappuccino) |
Who may qualify
- Ages
- 18 to 40 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
Key inclusion criteria (4 listed)
- Signed informed consent
- Healthy males and females
- BMI >18.5 and < 25 kg/m2
- Willing/able to consume all test foods and the standardized meals
Key exclusion criteria (9 listed)
- Smokers
- Diagnosed health condition (chronic or infectious disease)
- Taking nutritional supplements (e.g. vitamins, minerals) several times a week.
- Taking medication.
- Pregnant, lactating.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Mango AtaulfoIn this intervention, subjects consumed 150g of mango Ataulfo plus 150 ml of control beverage (Supportan® Drink Cappuccino). The addition of the control beverage has the purpose of providing energy intake and limiting the noise that the control beverage may contribute to the metabolomic profile in urine and serum. | Other | Mango Ataulfo |
| Avocado HassIn this intervention, subjects consumed 120g of avocado hass plus 150 ml of a control beverage (Supportan® Drink Cappuccino). The addition of the control beverage provides energy intake and limits the noise that the beverage may contribute to the metabolomic profile in urine and serum. | Other | Avocado Hass |
| NopalIn this intervention, subjects consumed 300g of cooked nopal and 150 ml of control beverage (Supportan® Drink Cappuccino). The addition of the control beverage provides energy intake and limits the noise that the beverage may contribute to the metabolic profile in urine and serum. | Other | Boiled Nopal |
| 3 corn tortillaIn this intervention, subjects consumed 3 corn tortillas and 150 ml of control beverage (Supportan® Drink Cappuccino). The addition of the control beverage provides energy intake and limits the noise that the beverage may contribute to the metabolic profile in urine and serum. | Other | Corn Tortilla |
| GuavaIn this intervention, subjects consumed 3 guavas and 150 ml of control beverage (Supportan® Drink Cappuccino). The addition of the control beverage provides energy intake and limits the noise that the beverage may contribute to the metabolic profile in urine and serum. | Other | Guava |
| AmaranthIn this intervention, subjects consumed 1/2 cup of amaranth and 150 ml of control beverage (Supportan® Drink Cappuccino). The addition of the control beverage provides energy intake and limits the noise that the beverage may contribute to the metabolic profile in urine and serum. | Other | Amaranth |
| Control Beverage (Supportan Drink ® Capuccino)In this intervention, subjects consumed 290ml of Supportan Drink ® Capuccino to act as a control for the metabolomic profiling in urine and serum. | Dietary supplement | Supportan® DKN Cappuccino |
Primary outcome
Metabolic profiling of urine samples after intake of mango, amaranth, nopal, corn tortilla, avocado, and guava, detected as mass-to-charge signals (cps) by an untargeted metabolomics approach over 24 hours post-intake.
Time frame: Before intake of foods 00 hours to 24 hours after intake.
Given the absence of a priori knowledge of specific urinary biomarkers of intake for mango, nopal, amaranth, avocado, corn tortilla, and guava, an untargeted metabolomics approach will be employed to identify them. As an exploratory approach, this methodology will determine the myriad of signals (mass-to-charge ratios) present in urine samples, which correspond to metabolites that become bioavailable after the intake of the test foods, collected at 0-1, 1-2, 4-6, 6-12, and 12-24 hours after intake. The analysis of the patterns in the metabolome will facilitate the discovery of potential biomarkers of intake.
Metabolic profiling of serum samples after intake of mango, amaranth, nopal, corn tortilla, avocado, and guava, detected as mass-to-charge signals (cps) by an untargeted metabolomics approach over 24 hours post-intake.
Time frame: Before intake of foods 00 hours to 24 hours after intake.
Given the absence of a priori knowledge of specific serum biomarkers of intake for mango, nopal, amaranth, avocado, corn tortilla, and guava, an untargeted metabolomics approach will be employed to identify them. As an exploratory approach, this methodology will determine the myriad of signals (mass-to-charge ratios) present in serum samples collected at baseline, 1 hour, 2 hours, 4 hours, 6 hours, and 24 hours after the intake of. The analysis of the patterns in the metabolome will facilitate the discovery of potential biomarkers of intake.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 Jun 2024.
- Background: PubMed 30121379Archer E, Marlow ML, Lavie CJ. Controversy and debate: Memory-Based Methods Paper 1: the fatal flaws of food frequency questionnaires and other memory-based dietary assessment methods. J Clin Epidemiol. 2018 Dec;104:113-124. doi: 10.1016/j.jclinepi.2018.08.003. Epub 2018 Aug 17.
- Background: PubMed 22071707Tinker LF, Sarto GE, Howard BV, Huang Y, Neuhouser ML, Mossavar-Rahmani Y, Beasley JM, Margolis KL, Eaton CB, Phillips LS, Prentice RL. Biomarker-calibrated dietary energy and protein intake associations with diabetes risk among postmenopausal women from the Women's Health Initiative. Am J Clin Nutr. 2011 Dec;94(6):1600-6. doi: 10.3945/ajcn.111.018648. Epub 2011 Nov 9.
- Background: PubMed 1962591Vanderslice JT, Higgs DJ. Vitamin C content of foods: sample variability. Am J Clin Nutr. 1991 Dec;54(6 Suppl):1323S-1327S. doi: 10.1093/ajcn/54.6.1323s.
- Background: PubMed 24390407Andersen 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.
- Background: PubMed 28556565Gibbons H, Michielsen CJR, Rundle M, Frost G, McNulty BA, Nugent AP, Walton J, Flynn A, Gibney MJ, Brennan L. Demonstration of the utility of biomarkers for dietary intake assessment; proline betaine as an example. Mol Nutr Food Res. 2017 Oct;61(10). doi: 10.1002/mnfr.201700037. Epub 2017 Jul 20.
- Background: PubMed 31141834Cuparencu C, Rinnan A, Dragsted LO. Combined Markers to Assess Meat Intake-Human Metabolomic Studies of Discovery and Validation. Mol Nutr Food Res. 2019 Sep;63(17):e1900106. doi: 10.1002/mnfr.201900106. Epub 2019 Jun 13.
- Background: PubMed 31240312Vazquez-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.
- Background: PubMed 31916678Giesbertz P, Brandl B, Lee YM, Hauner H, Daniel H, Skurk T. Specificity, Dose Dependency, and Kinetics of Markers of Chicken and Beef Intake Using Targeted Quantitative LC-MS/MS: A Human Intervention Trial. Mol Nutr Food Res. 2020 Mar;64(5):e1900921. doi: 10.1002/mnfr.201900921. Epub 2020 Jan 29.
- Background: PubMed 30176196Ulaszewska MM, Weinert CH, Trimigno A, Portmann R, Andres Lacueva C, Badertscher R, Brennan L, Brunius C, Bub A, Capozzi F, Cialie Rosso M, Cordero CE, Daniel H, Durand S, Egert B, Ferrario PG, Feskens EJM, Franceschi P, Garcia-Aloy M, Giacomoni F, Giesbertz P, Gonzalez-Dominguez R, Hanhineva K, Hemeryck LY, Kopka J, Kulling SE, Llorach R, Manach C, Mattivi F, Migne C, Munger LH, Ott B, Picone G, Pimentel G, Pujos-Guillot E, Riccadonna S, Rist MJ, Rombouts C, Rubert J, Skurk T, Sri Harsha PSC, Van Meulebroek L, Vanhaecke L, Vazquez-Fresno R, Wishart D, Vergeres G. Nutrimetabolomics: An Integrative Action for Metabolomic Analyses in Human Nutritional Studies. Mol Nutr Food Res. 2019 Jan;63(1):e1800384. doi: 10.1002/mnfr.201800384. Epub 2018 Oct 11.
- Background: PubMed 29861790Dragsted LO, Gao Q, Scalbert A, Vergeres G, Kolehmainen M, Manach C, Brennan L, Afman LA, Wishart DS, Andres Lacueva C, Garcia-Aloy M, Verhagen H, Feskens EJM, Pratico G. Validation of biomarkers of food intake-critical assessment of candidate biomarkers. Genes Nutr. 2018 May 30;13:14. doi: 10.1186/s12263-018-0603-9. eCollection 2018.
- Background: PubMed 26640139Barnes RC, Krenek KA, Meibohm B, Mertens-Talcott SU, Talcott ST. Urinary metabolites from mango (Mangifera indica L. cv. Keitt) galloyl derivatives and in vitro hydrolysis of gallotannins in physiological conditions. Mol Nutr Food Res. 2016 Mar;60(3):542-50. doi: 10.1002/mnfr.201500706. Epub 2016 Feb 2.
- Background: PubMed 34066494Kim H, Castellon-Chicas MJ, Arbizu S, Talcott ST, Drury NL, Smith S, Mertens-Talcott SU. Mango (Mangifera indica L.) Polyphenols: Anti-Inflammatory Intestinal Microbial Health Benefits, and Associated Mechanisms of Actions. Molecules. 2021 May 6;26(9):2732. doi: 10.3390/molecules26092732.
- The Food databaseLink provided by the sponsor.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Natalia Vázquez Manjarrez, PhD principal investigator
National Institute of Medical Sciences and Nutrition Salvador Zubirán
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Mango Ataulfo, Avocado Hass and Nopal in people with Nutrition, Healthy and Diet Habit, run by Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran at 1 site in Mexico.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 9 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 7 Jun 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Mexico. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Metabolic profiling of urine samples after intake of mango, amaranth, nopal, corn tortilla, avocado, and guava, detected as mass-to-charge signals (cps) by an untargeted metabolomics approach over 24 hours post-intake. (time frame: Before intake of foods 00 hours to 24 hours after intake.). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06449170, which also lists 27 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 7 Jun 2024.