Discovery and Validation of Banana Intake Biomarkers Using Untargeted Metabolomics in Human Intervention and Cross-sectional Studies

Banana is one of the most widely consumed fruits in the world. However, information regarding its health effects is scarce. Biomarkers of banana intake would allow a more accurate assessment of its consumption in nutrition studies. Using an untargeted metabolomics approach, we aimed to identify the...

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Veröffentlicht in:The Journal of nutrition 2019-10, Vol.149 (10), p.1701-1713
Hauptverfasser: Vázquez-Manjarrez, Natalia, Weinert, Christoph H, Ulaszewska, Maria M, Mack, Carina I, Micheau, Pierre, Pétéra, Mélanie, Durand, Stephanie, Pujos-Guillot, Estelle, Egert, Björn, Mattivi, Fulvio, Bub, Achim, Dragsted, Lars Ove, Kulling, Sabine E, Manach, Claudine
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container_end_page 1713
container_issue 10
container_start_page 1701
container_title The Journal of nutrition
container_volume 149
creator Vázquez-Manjarrez, Natalia
Weinert, Christoph H
Ulaszewska, Maria M
Mack, Carina I
Micheau, Pierre
Pétéra, Mélanie
Durand, Stephanie
Pujos-Guillot, Estelle
Egert, Björn
Mattivi, Fulvio
Bub, Achim
Dragsted, Lars Ove
Kulling, Sabine E
Manach, Claudine
description Banana is one of the most widely consumed fruits in the world. However, information regarding its health effects is scarce. Biomarkers of banana intake would allow a more accurate assessment of its consumption in nutrition studies. Using an untargeted metabolomics approach, we aimed to identify the banana-derived metabolites present in urine after consumption, including new candidate biomarkers of banana intake. A randomized controlled study with a crossover design was performed on 12 healthy subjects (6 men, 6 women, mean ± SD age: 30.0 ± 4.9 y; mean ± SD BMI: 22.5 ± 2.3 kg/m2). Subjects underwent 2 dietary interventions: 1) 250 mL control drink (Fresubin 2 kcal fiber, neutral flavor; Fresenius Kabi), and 2) 240 g banana + 150 mL control drink. Twenty-four-hour urine samples were collected and analyzed with ultra-performance liquid chromatography coupled to a quadrupole time-of-flight MS and 2-dimensional GC-MS. The discovered biomarkers were confirmed in a cross-sectional study [KarMeN (Karlsruhe Metabolomics and Nutrition study)] in which 78 subjects (mean BMI: 22.8; mean age: 47 y) were selected reflecting high intake (126–378 g/d), low intake (47.3–94.5 g/d), and nonconsumption of banana. The confirmed biomarkers were examined singly or in combinations, for established criteria of validation for biomarkers of food intake. We identified 33 potentially bioactive banana metabolites, of which 5 metabolites, methoxyeugenol glucuronide (MEUG-GLUC), dopamine sulfate (DOP-S), salsolinol sulfate, xanthurenic acid, and 6-hydroxy-1-methyl-1,2,3,4-tetrahydro-β-carboline sulfate, were confirmed as candidate intake biomarkers. We demonstrated that the combination of MEUG-GLUC and DOP-S performed best in predicting banana intake in high (AUCtest = 0.92) and low (AUCtest = 0.87) consumers. The new biomarkers met key criteria establishing their current applicability in nutrition and health research for assessing the occurrence of banana intake. Our metabolomics study in healthy men and women revealed new putative bioactive metabolites of banana and a combined biomarker of intake. These findings will help to better decipher the health effects of banana in future focused studies. This study was registered at clinicaltrials.gov as NCT03581955 and with the Ethical Committee for the Protection of Human Subjects Sud-Est 6 as CPP AU 1251, IDRCB 2016-A0013–48; the KarMeN study was registered with the German Clinical Trials Register (DRKS00004890). Details about the study can
doi_str_mv 10.1093/jn/nxz125
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However, information regarding its health effects is scarce. Biomarkers of banana intake would allow a more accurate assessment of its consumption in nutrition studies. Using an untargeted metabolomics approach, we aimed to identify the banana-derived metabolites present in urine after consumption, including new candidate biomarkers of banana intake. A randomized controlled study with a crossover design was performed on 12 healthy subjects (6 men, 6 women, mean ± SD age: 30.0 ± 4.9 y; mean ± SD BMI: 22.5 ± 2.3 kg/m2). Subjects underwent 2 dietary interventions: 1) 250 mL control drink (Fresubin 2 kcal fiber, neutral flavor; Fresenius Kabi), and 2) 240 g banana + 150 mL control drink. Twenty-four-hour urine samples were collected and analyzed with ultra-performance liquid chromatography coupled to a quadrupole time-of-flight MS and 2-dimensional GC-MS. The discovered biomarkers were confirmed in a cross-sectional study [KarMeN (Karlsruhe Metabolomics and Nutrition study)] in which 78 subjects (mean BMI: 22.8; mean age: 47 y) were selected reflecting high intake (126–378 g/d), low intake (47.3–94.5 g/d), and nonconsumption of banana. The confirmed biomarkers were examined singly or in combinations, for established criteria of validation for biomarkers of food intake. We identified 33 potentially bioactive banana metabolites, of which 5 metabolites, methoxyeugenol glucuronide (MEUG-GLUC), dopamine sulfate (DOP-S), salsolinol sulfate, xanthurenic acid, and 6-hydroxy-1-methyl-1,2,3,4-tetrahydro-β-carboline sulfate, were confirmed as candidate intake biomarkers. We demonstrated that the combination of MEUG-GLUC and DOP-S performed best in predicting banana intake in high (AUCtest = 0.92) and low (AUCtest = 0.87) consumers. The new biomarkers met key criteria establishing their current applicability in nutrition and health research for assessing the occurrence of banana intake. Our metabolomics study in healthy men and women revealed new putative bioactive metabolites of banana and a combined biomarker of intake. These findings will help to better decipher the health effects of banana in future focused studies. This study was registered at clinicaltrials.gov as NCT03581955 and with the Ethical Committee for the Protection of Human Subjects Sud-Est 6 as CPP AU 1251, IDRCB 2016-A0013–48; the KarMeN study was registered with the German Clinical Trials Register (DRKS00004890). 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However, information regarding its health effects is scarce. Biomarkers of banana intake would allow a more accurate assessment of its consumption in nutrition studies. Using an untargeted metabolomics approach, we aimed to identify the banana-derived metabolites present in urine after consumption, including new candidate biomarkers of banana intake. A randomized controlled study with a crossover design was performed on 12 healthy subjects (6 men, 6 women, mean ± SD age: 30.0 ± 4.9 y; mean ± SD BMI: 22.5 ± 2.3 kg/m2). Subjects underwent 2 dietary interventions: 1) 250 mL control drink (Fresubin 2 kcal fiber, neutral flavor; Fresenius Kabi), and 2) 240 g banana + 150 mL control drink. Twenty-four-hour urine samples were collected and analyzed with ultra-performance liquid chromatography coupled to a quadrupole time-of-flight MS and 2-dimensional GC-MS. The discovered biomarkers were confirmed in a cross-sectional study [KarMeN (Karlsruhe Metabolomics and Nutrition study)] in which 78 subjects (mean BMI: 22.8; mean age: 47 y) were selected reflecting high intake (126–378 g/d), low intake (47.3–94.5 g/d), and nonconsumption of banana. The confirmed biomarkers were examined singly or in combinations, for established criteria of validation for biomarkers of food intake. We identified 33 potentially bioactive banana metabolites, of which 5 metabolites, methoxyeugenol glucuronide (MEUG-GLUC), dopamine sulfate (DOP-S), salsolinol sulfate, xanthurenic acid, and 6-hydroxy-1-methyl-1,2,3,4-tetrahydro-β-carboline sulfate, were confirmed as candidate intake biomarkers. We demonstrated that the combination of MEUG-GLUC and DOP-S performed best in predicting banana intake in high (AUCtest = 0.92) and low (AUCtest = 0.87) consumers. The new biomarkers met key criteria establishing their current applicability in nutrition and health research for assessing the occurrence of banana intake. Our metabolomics study in healthy men and women revealed new putative bioactive metabolites of banana and a combined biomarker of intake. These findings will help to better decipher the health effects of banana in future focused studies. This study was registered at clinicaltrials.gov as NCT03581955 and with the Ethical Committee for the Protection of Human Subjects Sud-Est 6 as CPP AU 1251, IDRCB 2016-A0013–48; the KarMeN study was registered with the German Clinical Trials Register (DRKS00004890). 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Weinert, Christoph H ; Ulaszewska, Maria M ; Mack, Carina I ; Micheau, Pierre ; Pétéra, Mélanie ; Durand, Stephanie ; Pujos-Guillot, Estelle ; Egert, Björn ; Mattivi, Fulvio ; Bub, Achim ; Dragsted, Lars Ove ; Kulling, Sabine E ; Manach, Claudine</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c455t-3ba8bf165302f388a23ad11277ee0702004dece80243bb949faec5d63d68771f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Adult</topic><topic>Analysis of Variance</topic><topic>banana</topic><topic>Bananas</topic><topic>Bioactive compounds</topic><topic>Biological activity</topic><topic>Biomarkers</topic><topic>Biomarkers - blood</topic><topic>Biomarkers - urine</topic><topic>biomarkers of intake</topic><topic>Chromatography, Liquid</topic><topic>Clinical trials</topic><topic>Control methods</topic><topic>Cross-Over Studies</topic><topic>Cross-Sectional Studies</topic><topic>Diet</topic><topic>dietary assessment</topic><topic>Dopamine</topic><topic>Female</topic><topic>Flavor</topic><topic>Food and Nutrition</topic><topic>Food intake</topic><topic>Gas Chromatography-Mass Spectrometry</topic><topic>Health</topic><topic>Humans</topic><topic>Life Sciences</topic><topic>Liquid chromatography</topic><topic>Male</topic><topic>Mass Spectrometry</topic><topic>Metabolites</topic><topic>Metabolomics</topic><topic>methoxyeugenol</topic><topic>Middle Aged</topic><topic>Musa</topic><topic>nutrimetabolomics</topic><topic>Nutrition</topic><topic>Performance prediction</topic><topic>Quadrupoles</topic><topic>Reproducibility of Results</topic><topic>Salsolinol</topic><topic>Sulfates</topic><topic>tetrahydro-β-carbolines</topic><topic>untargeted</topic><topic>Urine</topic><topic>Xanthurenic acid</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vázquez-Manjarrez, Natalia</creatorcontrib><creatorcontrib>Weinert, Christoph H</creatorcontrib><creatorcontrib>Ulaszewska, Maria M</creatorcontrib><creatorcontrib>Mack, Carina I</creatorcontrib><creatorcontrib>Micheau, Pierre</creatorcontrib><creatorcontrib>Pétéra, Mélanie</creatorcontrib><creatorcontrib>Durand, Stephanie</creatorcontrib><creatorcontrib>Pujos-Guillot, Estelle</creatorcontrib><creatorcontrib>Egert, Björn</creatorcontrib><creatorcontrib>Mattivi, Fulvio</creatorcontrib><creatorcontrib>Bub, Achim</creatorcontrib><creatorcontrib>Dragsted, Lars Ove</creatorcontrib><creatorcontrib>Kulling, Sabine E</creatorcontrib><creatorcontrib>Manach, Claudine</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Health &amp; 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However, information regarding its health effects is scarce. Biomarkers of banana intake would allow a more accurate assessment of its consumption in nutrition studies. Using an untargeted metabolomics approach, we aimed to identify the banana-derived metabolites present in urine after consumption, including new candidate biomarkers of banana intake. A randomized controlled study with a crossover design was performed on 12 healthy subjects (6 men, 6 women, mean ± SD age: 30.0 ± 4.9 y; mean ± SD BMI: 22.5 ± 2.3 kg/m2). Subjects underwent 2 dietary interventions: 1) 250 mL control drink (Fresubin 2 kcal fiber, neutral flavor; Fresenius Kabi), and 2) 240 g banana + 150 mL control drink. Twenty-four-hour urine samples were collected and analyzed with ultra-performance liquid chromatography coupled to a quadrupole time-of-flight MS and 2-dimensional GC-MS. The discovered biomarkers were confirmed in a cross-sectional study [KarMeN (Karlsruhe Metabolomics and Nutrition study)] in which 78 subjects (mean BMI: 22.8; mean age: 47 y) were selected reflecting high intake (126–378 g/d), low intake (47.3–94.5 g/d), and nonconsumption of banana. The confirmed biomarkers were examined singly or in combinations, for established criteria of validation for biomarkers of food intake. We identified 33 potentially bioactive banana metabolites, of which 5 metabolites, methoxyeugenol glucuronide (MEUG-GLUC), dopamine sulfate (DOP-S), salsolinol sulfate, xanthurenic acid, and 6-hydroxy-1-methyl-1,2,3,4-tetrahydro-β-carboline sulfate, were confirmed as candidate intake biomarkers. We demonstrated that the combination of MEUG-GLUC and DOP-S performed best in predicting banana intake in high (AUCtest = 0.92) and low (AUCtest = 0.87) consumers. The new biomarkers met key criteria establishing their current applicability in nutrition and health research for assessing the occurrence of banana intake. Our metabolomics study in healthy men and women revealed new putative bioactive metabolites of banana and a combined biomarker of intake. These findings will help to better decipher the health effects of banana in future focused studies. This study was registered at clinicaltrials.gov as NCT03581955 and with the Ethical Committee for the Protection of Human Subjects Sud-Est 6 as CPP AU 1251, IDRCB 2016-A0013–48; the KarMeN study was registered with the German Clinical Trials Register (DRKS00004890). Details about the study can be obtained from https://www.drks.de.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>31240312</pmid><doi>10.1093/jn/nxz125</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-1779-6901</orcidid><orcidid>https://orcid.org/0000-0001-6907-5519</orcidid><orcidid>https://orcid.org/0000-0002-4693-5712</orcidid><orcidid>https://orcid.org/0000-0003-4935-5876</orcidid><orcidid>https://orcid.org/0000-0002-9956-2702</orcidid><orcidid>https://orcid.org/0000-0002-9250-5537</orcidid><orcidid>https://orcid.org/0000-0003-0609-6317</orcidid><orcidid>https://orcid.org/0000-0003-3482-3526</orcidid><orcidid>https://orcid.org/0000-0002-0929-2359</orcidid><orcidid>https://orcid.org/0000-0001-8617-7947</orcidid><orcidid>https://orcid.org/0000-0002-1015-8667</orcidid><orcidid>https://orcid.org/0000-0003-1094-3363</orcidid><oa>free_for_read</oa></addata></record>
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ispartof The Journal of nutrition, 2019-10, Vol.149 (10), p.1701-1713
issn 0022-3166
1541-6100
language eng
recordid cdi_hal_primary_oai_HAL_hal_02332545v1
source MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Alma/SFX Local Collection
subjects Adult
Analysis of Variance
banana
Bananas
Bioactive compounds
Biological activity
Biomarkers
Biomarkers - blood
Biomarkers - urine
biomarkers of intake
Chromatography, Liquid
Clinical trials
Control methods
Cross-Over Studies
Cross-Sectional Studies
Diet
dietary assessment
Dopamine
Female
Flavor
Food and Nutrition
Food intake
Gas Chromatography-Mass Spectrometry
Health
Humans
Life Sciences
Liquid chromatography
Male
Mass Spectrometry
Metabolites
Metabolomics
methoxyeugenol
Middle Aged
Musa
nutrimetabolomics
Nutrition
Performance prediction
Quadrupoles
Reproducibility of Results
Salsolinol
Sulfates
tetrahydro-β-carbolines
untargeted
Urine
Xanthurenic acid
title Discovery and Validation of Banana Intake Biomarkers Using Untargeted Metabolomics in Human Intervention and Cross-sectional Studies
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