Identification of Milk and Cheese Intake Biomarkers in Healthy Adults Reveals High Interindividual Variability of Lewis System–Related Oligosaccharides
The use of biomarkers of food intake (BFIs) in blood and urine has shown great promise for assessing dietary intake and complementing traditional dietary assessment tools whose use is prone to misreporting. Untargeted LC-MS metabolomics was applied to identify candidate BFIs for assessing the intake...
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creator | Pimentel, Grégory Burnand, David Münger, Linda H Pralong, François P Vionnet, Nathalie Portmann, Reto Vergères, Guy |
description | The use of biomarkers of food intake (BFIs) in blood and urine has shown great promise for assessing dietary intake and complementing traditional dietary assessment tools whose use is prone to misreporting.
Untargeted LC-MS metabolomics was applied to identify candidate BFIs for assessing the intake of milk and cheese and to explore the metabolic response to the ingestion of these foods.
A randomized controlled crossover study was conducted in healthy adults [5 women, 6 men; age: 23.6 ± 5.0 y; BMI (kg/m2): 22.1 ± 1.7]. After a single isocaloric intake of milk (600 mL), cheese (100 g), or soy-based drink (600 mL), serum and urine samples were collected postprandially up to 6 h and after fasting after 24 h. Untargeted metabolomics was conducted using LC-MS. Discriminant metabolites were selected in serum by multivariate statistical analysis, and their mass distribution and postprandial kinetics were compared.
Serum metabolites discriminant for cheese intake had a significantly lower mass distribution than metabolites characterizing milk intake (P = 4.1 × 10-4). Candidate BFIs for milk or cheese included saccharides, a hydroxy acid, amino acids, amino acid derivatives, and dipeptides. Two serum oligosaccharides, blood group H disaccharide (BGH) and Lewis A trisaccharide (LeA), specifically reflected milk intake but with high interindividual variability. The 2 oligosaccharides showed related but opposing trends: subjects showing an increase in either oligosaccharide did not show any increase in the other oligosaccharide. This result was confirmed in urine.
New candidate BFIs for milk or cheese could be identified in healthy adults, most of which were related to protein metabolism. The increase in serum of LeA and BGH after cow-milk intake in adults calls for further investigations considering the beneficial health effects on newborns of such oligosaccharides in maternal milk. The trial is registered at clinicaltrials.gov as NCT02705560. |
doi_str_mv | 10.1093/jn/nxaa029 |
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Untargeted LC-MS metabolomics was applied to identify candidate BFIs for assessing the intake of milk and cheese and to explore the metabolic response to the ingestion of these foods.
A randomized controlled crossover study was conducted in healthy adults [5 women, 6 men; age: 23.6 ± 5.0 y; BMI (kg/m2): 22.1 ± 1.7]. After a single isocaloric intake of milk (600 mL), cheese (100 g), or soy-based drink (600 mL), serum and urine samples were collected postprandially up to 6 h and after fasting after 24 h. Untargeted metabolomics was conducted using LC-MS. Discriminant metabolites were selected in serum by multivariate statistical analysis, and their mass distribution and postprandial kinetics were compared.
Serum metabolites discriminant for cheese intake had a significantly lower mass distribution than metabolites characterizing milk intake (P = 4.1 × 10-4). Candidate BFIs for milk or cheese included saccharides, a hydroxy acid, amino acids, amino acid derivatives, and dipeptides. Two serum oligosaccharides, blood group H disaccharide (BGH) and Lewis A trisaccharide (LeA), specifically reflected milk intake but with high interindividual variability. The 2 oligosaccharides showed related but opposing trends: subjects showing an increase in either oligosaccharide did not show any increase in the other oligosaccharide. This result was confirmed in urine.
New candidate BFIs for milk or cheese could be identified in healthy adults, most of which were related to protein metabolism. The increase in serum of LeA and BGH after cow-milk intake in adults calls for further investigations considering the beneficial health effects on newborns of such oligosaccharides in maternal milk. The trial is registered at clinicaltrials.gov as NCT02705560.</description><identifier>ISSN: 0022-3166</identifier><identifier>EISSN: 1541-6100</identifier><identifier>DOI: 10.1093/jn/nxaa029</identifier><identifier>PMID: 32133503</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adolescent ; Adult ; Adults ; Amino acids ; Animals ; biomarker ; Biomarkers ; Biomarkers - blood ; Blood groups ; Carbohydrates ; Cheese ; Control methods ; Cow's milk ; Cross-Over Studies ; dairy ; Dairy products ; Diet ; Dietary intake ; Disaccharides ; Female ; Food intake ; Genomics, Proteomics, and Metabolomics ; Humans ; Hydroxy acids ; Ingestion ; Lewis antigen ; Lewis system ; Male ; Mass distribution ; Men ; Metabolic response ; Metabolism ; Metabolites ; Metabolomics ; Milk ; Multivariate statistical analysis ; Neonates ; Oligosaccharides ; Oligosaccharides - blood ; Oligosaccharides - chemistry ; Oligosaccharides - metabolism ; postprandial ; Protein metabolism ; Protein turnover ; Saccharides ; serum metabolome ; soy ; Statistical analysis ; Statistical methods ; Urine ; Young Adult</subject><ispartof>The Journal of nutrition, 2020-05, Vol.150 (5), p.1058-1067</ispartof><rights>2020 American Society for Nutrition.</rights><rights>Copyright © The Author(s) 2020. 2018</rights><rights>Copyright © The Author(s) 2020.</rights><rights>Copyright American Institute of Nutrition May 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c547t-85b1f3f540e3f21729343a8332c83edebf7820f55af8d0170a264b202c73f1db3</citedby><cites>FETCH-LOGICAL-c547t-85b1f3f540e3f21729343a8332c83edebf7820f55af8d0170a264b202c73f1db3</cites><orcidid>0000-0001-8979-7439 ; 0000-0002-1695-9764 ; 0000-0002-5420-8216 ; 0000-0003-3687-3519 ; 0000-0003-4574-0590 ; 0000-0002-0550-1651</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32133503$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Pimentel, Grégory</creatorcontrib><creatorcontrib>Burnand, David</creatorcontrib><creatorcontrib>Münger, Linda H</creatorcontrib><creatorcontrib>Pralong, François P</creatorcontrib><creatorcontrib>Vionnet, Nathalie</creatorcontrib><creatorcontrib>Portmann, Reto</creatorcontrib><creatorcontrib>Vergères, Guy</creatorcontrib><title>Identification of Milk and Cheese Intake Biomarkers in Healthy Adults Reveals High Interindividual Variability of Lewis System–Related Oligosaccharides</title><title>The Journal of nutrition</title><addtitle>J Nutr</addtitle><description>The use of biomarkers of food intake (BFIs) in blood and urine has shown great promise for assessing dietary intake and complementing traditional dietary assessment tools whose use is prone to misreporting.
Untargeted LC-MS metabolomics was applied to identify candidate BFIs for assessing the intake of milk and cheese and to explore the metabolic response to the ingestion of these foods.
A randomized controlled crossover study was conducted in healthy adults [5 women, 6 men; age: 23.6 ± 5.0 y; BMI (kg/m2): 22.1 ± 1.7]. After a single isocaloric intake of milk (600 mL), cheese (100 g), or soy-based drink (600 mL), serum and urine samples were collected postprandially up to 6 h and after fasting after 24 h. Untargeted metabolomics was conducted using LC-MS. Discriminant metabolites were selected in serum by multivariate statistical analysis, and their mass distribution and postprandial kinetics were compared.
Serum metabolites discriminant for cheese intake had a significantly lower mass distribution than metabolites characterizing milk intake (P = 4.1 × 10-4). Candidate BFIs for milk or cheese included saccharides, a hydroxy acid, amino acids, amino acid derivatives, and dipeptides. Two serum oligosaccharides, blood group H disaccharide (BGH) and Lewis A trisaccharide (LeA), specifically reflected milk intake but with high interindividual variability. The 2 oligosaccharides showed related but opposing trends: subjects showing an increase in either oligosaccharide did not show any increase in the other oligosaccharide. This result was confirmed in urine.
New candidate BFIs for milk or cheese could be identified in healthy adults, most of which were related to protein metabolism. The increase in serum of LeA and BGH after cow-milk intake in adults calls for further investigations considering the beneficial health effects on newborns of such oligosaccharides in maternal milk. The trial is registered at clinicaltrials.gov as NCT02705560.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Adults</subject><subject>Amino acids</subject><subject>Animals</subject><subject>biomarker</subject><subject>Biomarkers</subject><subject>Biomarkers - blood</subject><subject>Blood groups</subject><subject>Carbohydrates</subject><subject>Cheese</subject><subject>Control methods</subject><subject>Cow's milk</subject><subject>Cross-Over Studies</subject><subject>dairy</subject><subject>Dairy products</subject><subject>Diet</subject><subject>Dietary intake</subject><subject>Disaccharides</subject><subject>Female</subject><subject>Food intake</subject><subject>Genomics, Proteomics, and Metabolomics</subject><subject>Humans</subject><subject>Hydroxy acids</subject><subject>Ingestion</subject><subject>Lewis antigen</subject><subject>Lewis system</subject><subject>Male</subject><subject>Mass distribution</subject><subject>Men</subject><subject>Metabolic response</subject><subject>Metabolism</subject><subject>Metabolites</subject><subject>Metabolomics</subject><subject>Milk</subject><subject>Multivariate statistical analysis</subject><subject>Neonates</subject><subject>Oligosaccharides</subject><subject>Oligosaccharides - blood</subject><subject>Oligosaccharides - chemistry</subject><subject>Oligosaccharides - metabolism</subject><subject>postprandial</subject><subject>Protein metabolism</subject><subject>Protein turnover</subject><subject>Saccharides</subject><subject>serum metabolome</subject><subject>soy</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>Urine</subject><subject>Young Adult</subject><issn>0022-3166</issn><issn>1541-6100</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><sourceid>EIF</sourceid><recordid>eNp9kd2KEzEUx4Mo7lq98QEkIIIIdfMx05neCGtRW6gsrB-3IZOcaU87TWqSqfbOd_DK1_NJTGldVMSrQPI7v_zPOYQ85Ow5Z2N5sXIX7ovWTIxvkXNeFnw44ozdJueMCTGUfDQ6I_diXDHGeDGu75IzKbiUJZPn5PvMgkvYotEJvaO-pW-xW1PtLJ0sASLQmUt6DfQl-o0OawiRoqNT0F1a7uml7bsU6TXs8kWkU1wsDwUQ0Fncoe11Rz_qgLrBDtP-4J_DZ4z03T4m2Pz4-u0aOp3A0qsOFz5qY5YZtxDvkzttVsKD0zkgH16_ej-ZDudXb2aTy_nQlEWVhnXZ8Fa2ZcFAtoJXYiwLqWsphaklWGjaqhasLUvd1pbximkxKhrBhKlky20jB-TF0bvtmw1Yk8cRdKe2AXO7e-U1qj9fHC7Vwu9Uxcd1_i0Lnp4EwX_qISa1wWig67QD30clZMXrUSlyrgF5_Be68n1wuT0lCsbroqqZyNSzI2WCjzFAexOGM3XYuFo5ddp4hh_9Hv8G_bXiDDw5Ar7f_l9UHDnIw94hBBUNgjNgMYBJynr8V9lPILLKgg</recordid><startdate>20200501</startdate><enddate>20200501</enddate><creator>Pimentel, Grégory</creator><creator>Burnand, David</creator><creator>Münger, Linda H</creator><creator>Pralong, François P</creator><creator>Vionnet, Nathalie</creator><creator>Portmann, Reto</creator><creator>Vergères, Guy</creator><general>Elsevier Inc</general><general>Oxford University Press</general><general>American Institute of Nutrition</general><scope>6I.</scope><scope>AAFTH</scope><scope>TOX</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-8979-7439</orcidid><orcidid>https://orcid.org/0000-0002-1695-9764</orcidid><orcidid>https://orcid.org/0000-0002-5420-8216</orcidid><orcidid>https://orcid.org/0000-0003-3687-3519</orcidid><orcidid>https://orcid.org/0000-0003-4574-0590</orcidid><orcidid>https://orcid.org/0000-0002-0550-1651</orcidid></search><sort><creationdate>20200501</creationdate><title>Identification of Milk and Cheese Intake Biomarkers in Healthy Adults Reveals High Interindividual Variability of Lewis System–Related Oligosaccharides</title><author>Pimentel, Grégory ; Burnand, David ; Münger, Linda H ; Pralong, François P ; Vionnet, Nathalie ; Portmann, Reto ; Vergères, Guy</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c547t-85b1f3f540e3f21729343a8332c83edebf7820f55af8d0170a264b202c73f1db3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Adults</topic><topic>Amino acids</topic><topic>Animals</topic><topic>biomarker</topic><topic>Biomarkers</topic><topic>Biomarkers - blood</topic><topic>Blood groups</topic><topic>Carbohydrates</topic><topic>Cheese</topic><topic>Control methods</topic><topic>Cow's milk</topic><topic>Cross-Over Studies</topic><topic>dairy</topic><topic>Dairy products</topic><topic>Diet</topic><topic>Dietary intake</topic><topic>Disaccharides</topic><topic>Female</topic><topic>Food intake</topic><topic>Genomics, Proteomics, and Metabolomics</topic><topic>Humans</topic><topic>Hydroxy acids</topic><topic>Ingestion</topic><topic>Lewis antigen</topic><topic>Lewis system</topic><topic>Male</topic><topic>Mass distribution</topic><topic>Men</topic><topic>Metabolic response</topic><topic>Metabolism</topic><topic>Metabolites</topic><topic>Metabolomics</topic><topic>Milk</topic><topic>Multivariate statistical analysis</topic><topic>Neonates</topic><topic>Oligosaccharides</topic><topic>Oligosaccharides - blood</topic><topic>Oligosaccharides - chemistry</topic><topic>Oligosaccharides - metabolism</topic><topic>postprandial</topic><topic>Protein metabolism</topic><topic>Protein turnover</topic><topic>Saccharides</topic><topic>serum metabolome</topic><topic>soy</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><topic>Urine</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pimentel, Grégory</creatorcontrib><creatorcontrib>Burnand, David</creatorcontrib><creatorcontrib>Münger, Linda H</creatorcontrib><creatorcontrib>Pralong, François P</creatorcontrib><creatorcontrib>Vionnet, Nathalie</creatorcontrib><creatorcontrib>Portmann, Reto</creatorcontrib><creatorcontrib>Vergères, Guy</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Oxford Journals Open Access Collection</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 & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>The Journal of nutrition</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pimentel, Grégory</au><au>Burnand, David</au><au>Münger, Linda H</au><au>Pralong, François P</au><au>Vionnet, Nathalie</au><au>Portmann, Reto</au><au>Vergères, Guy</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of Milk and Cheese Intake Biomarkers in Healthy Adults Reveals High Interindividual Variability of Lewis System–Related Oligosaccharides</atitle><jtitle>The Journal of nutrition</jtitle><addtitle>J Nutr</addtitle><date>2020-05-01</date><risdate>2020</risdate><volume>150</volume><issue>5</issue><spage>1058</spage><epage>1067</epage><pages>1058-1067</pages><issn>0022-3166</issn><eissn>1541-6100</eissn><abstract>The use of biomarkers of food intake (BFIs) in blood and urine has shown great promise for assessing dietary intake and complementing traditional dietary assessment tools whose use is prone to misreporting.
Untargeted LC-MS metabolomics was applied to identify candidate BFIs for assessing the intake of milk and cheese and to explore the metabolic response to the ingestion of these foods.
A randomized controlled crossover study was conducted in healthy adults [5 women, 6 men; age: 23.6 ± 5.0 y; BMI (kg/m2): 22.1 ± 1.7]. After a single isocaloric intake of milk (600 mL), cheese (100 g), or soy-based drink (600 mL), serum and urine samples were collected postprandially up to 6 h and after fasting after 24 h. Untargeted metabolomics was conducted using LC-MS. Discriminant metabolites were selected in serum by multivariate statistical analysis, and their mass distribution and postprandial kinetics were compared.
Serum metabolites discriminant for cheese intake had a significantly lower mass distribution than metabolites characterizing milk intake (P = 4.1 × 10-4). Candidate BFIs for milk or cheese included saccharides, a hydroxy acid, amino acids, amino acid derivatives, and dipeptides. Two serum oligosaccharides, blood group H disaccharide (BGH) and Lewis A trisaccharide (LeA), specifically reflected milk intake but with high interindividual variability. The 2 oligosaccharides showed related but opposing trends: subjects showing an increase in either oligosaccharide did not show any increase in the other oligosaccharide. This result was confirmed in urine.
New candidate BFIs for milk or cheese could be identified in healthy adults, most of which were related to protein metabolism. The increase in serum of LeA and BGH after cow-milk intake in adults calls for further investigations considering the beneficial health effects on newborns of such oligosaccharides in maternal milk. The trial is registered at clinicaltrials.gov as NCT02705560.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>32133503</pmid><doi>10.1093/jn/nxaa029</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-8979-7439</orcidid><orcidid>https://orcid.org/0000-0002-1695-9764</orcidid><orcidid>https://orcid.org/0000-0002-5420-8216</orcidid><orcidid>https://orcid.org/0000-0003-3687-3519</orcidid><orcidid>https://orcid.org/0000-0003-4574-0590</orcidid><orcidid>https://orcid.org/0000-0002-0550-1651</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adolescent Adult Adults Amino acids Animals biomarker Biomarkers Biomarkers - blood Blood groups Carbohydrates Cheese Control methods Cow's milk Cross-Over Studies dairy Dairy products Diet Dietary intake Disaccharides Female Food intake Genomics, Proteomics, and Metabolomics Humans Hydroxy acids Ingestion Lewis antigen Lewis system Male Mass distribution Men Metabolic response Metabolism Metabolites Metabolomics Milk Multivariate statistical analysis Neonates Oligosaccharides Oligosaccharides - blood Oligosaccharides - chemistry Oligosaccharides - metabolism postprandial Protein metabolism Protein turnover Saccharides serum metabolome soy Statistical analysis Statistical methods Urine Young Adult |
title | Identification of Milk and Cheese Intake Biomarkers in Healthy Adults Reveals High Interindividual Variability of Lewis System–Related Oligosaccharides |
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