Dataset Information

Identification of Milk and Cheese Intake Biomarkers in Healthy Adults Reveals High Interindividual Variability of Lewis System-Related Oligosaccharides.

ABSTRACT: BACKGROUND: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. OBJECTIVE: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. METHODS: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. RESULTS: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. CONCLUSIONS: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.

SUBMITTER: Pimentel G

PROVIDER: S-EPMC7198293 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Identification of Milk and Cheese Intake Biomarkers in Healthy Adults Reveals High Interindividual Variability of Lewis System-Related Oligosaccharides.

Pimentel Grégory G Burnand David D Münger Linda H LH Pralong François P FP Vionnet Nathalie N Portmann Reto R Vergères Guy G

The Journal of nutrition 20200501 5

<h4>Background</h4>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.<h4>Objective</h4>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.<h4>Methods</h4>A randomized controlled crossover study was conducted in h ...[more]

PMID: 32133503

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Project description:BackgroundA growing number of cohort studies revealed an inverse association between cheese intake and cardiovascular diseases, yet the causal relationship is unclear.ObjectiveTo assess the causal relationship between cheese intake, and cardiovascular diseases and cardiovascular biomarkers.MethodsA two-sample Mendelian randomization (MR) analysis based on publicly available genome-wide association studies was employed to infer the causal relationship. The effect estimates were calculated using the random-effects inverse-variance-weighted method.ResultsCheese intake per standard deviation increase causally reduced the risks of type 2 diabetes (odds ratio (OR) = 0.46; 95% confidence interval (CI), 0.34-0.63; p = 1.02 × 10-6), heart failure (OR = 0.62; 95% CI, 0.49-0.79; p = 0.0001), coronary heart disease (OR = 0.65; 95% CI, 0.53-0.79; p = 2.01 × 10-5), hypertension (OR = 0.67; 95% CI, 0.53-0.84; p = 0.001), and ischemic stroke (OR = 0.76; 95% CI, 0.63-0.91; p = 0.003). Suggestive evidence of an inverse association between cheese intake and peripheral artery disease was also observed. No associations were observed for atrial fibrillation, cardiac death, pulmonary embolism, or transient ischemic attack. The better prognosis associated with cheese intake may be explained by lower body mass index (BMI; effect estimate = -0.58; 95% CI, from -0.88 to -0.27; p = 0.0002), waist circumference (effect estimate = -0.49; 95% CI, from -0.76 to -0.23; p = 0.0003), triglycerides (effect estimate = -0.33; 95% CI, from -0.50 to -0.17; p = 4.91 × 10-5), and fasting glucose (effect estimate = -0.20; 95% CI, from -0.33 to -0.07; p = 0.0003). There was suggestive evidence of a positive association between cheese intake and high-density lipoprotein. No influences were observed for blood pressure or inflammation biomarkers.ConclusionsThis two-sample MR analysis found causally inverse associations between cheese intake and type 2 diabetes, heart failure, coronary heart disease, hypertension, and ischemic stroke.

Dataset Information

Identification of Milk and Cheese Intake Biomarkers in Healthy Adults Reveals High Interindividual Variability of Lewis System-Related Oligosaccharides.

Publications

Identification of Milk and Cheese Intake Biomarkers in Healthy Adults Reveals High Interindividual Variability of Lewis System-Related Oligosaccharides.

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