Signatures métaboliques résultant de l'ingestion de lait ou de yaourt chez l'Homme : effet de l'âge

Metabolic Signatures Resulting From Acute (Postprandial) Intake Of Milk Or Yoghurt In Men : Effect Of Age

• Auteur / Autrice : Jinyoung Kim
• Direction : Sergio Polakof, Dominique Dardevet
• Type : Thèse de doctorat
• Discipline(s) : Nutrition
• Date : Soutenance le 05/10/2021
• Etablissement(s) : Université Clermont Auvergne (2021-...)
• Ecole(s) doctorale(s) : École doctorale des sciences de la vie, santé, agronomie, environnement (Clermont-Ferrand)
• Partenaire(s) de recherche : Laboratoire : Unité de nutrition humaine (Clermont-Ferrand)
• Jury : Président / Présidente : Stéphane Walrand
• Jury : Examinateurs / Examinatrices : Guy Vergérès, Yves Le Loir, Anne-Marie Davila, Corinne Marmonier, Kathryn Burton-Pimentel
• Jury : Rapporteur / Rapporteuse : Augustin Scalbert

Mots clés

Mots clés contrôlés

Effets de l'âge

Métabolisme

Produits laitiers

Mots clés libres

Produits laitiers

Dairy

Fermentation

Metabolomics

Biomarkers

Ageing

Résumé

Résumé indisponible.

Numerous studies have suggested that the intake of different types of dairy products,particularly fermented ones, are correlated with numerous health benefits. However, thesestudies often found heterogeneous results, which could be explained by inaccuratemeasurementof different type of dairy intake as well as the physiological capacities and condition of thestudied populations, such as the older. To fully elucidate associations betweendairy intake andhuman health, it is necessary to achieve more accurate measurement of specificdairy intake byidentifying specific intake biomarkers and by including the impact of modifiedmetabolism asobserved during aging. Therefore, the aim of this PhD thesis was to use metabolomics toidentify candidate biomarkers of milk and yoghurt intakes in healthy young andolder men byinvestigating the postprandial responses to those dairy products. The effect of age on themetabolic signatures associated with dairy intake (postprandial and fasting with restriction ofdairy and fermented food from diet) was also investigated.Through a randomised, controlled and crossover study, a total of 31 identifiedmetabolites showed that modification of the composition and texture of milk by fermentationcould differentiate postprandial responses to the intake of the two products. We confirmed somemetabolites that were previously suggested as candidate biomarkers of dairy intake includinglactose, galactonate, and galactitol (higher after milk intake) or 3-phenyllactic acid (higher afteryoghurt intake, but rather considered as a biomarker of fermented food). Other metabolites, likeshingosine-1-phosphate and an unidentified disaccharide, should be further studied forvalidation as potential biomarkers of milk and yoghurt intake, respectively.We also found that several metabolites showed changes likely explained by a healthyageing process, including delays in the postprandial response of several lipids, galactonate andlactose as well as a lower glycocholic acid response. These results highlight the importance oftaking into account both, the product- and population specificities when exploring biomarkersof food intake.The dietary shift induced by the exclusion of dairy products and the reduction offermented foods intake from the diet during 3 weeks before the postprandial challenges, wasaccompanied by specific modifications in the composition of the gut microbiota, including anincreased relative abundance of Akkermansia muciniphila and a decreased relative abundanceof bacteria of Clostridiales order. Each of these changes in the gut microbiota might have alsocontributed to the effects of the dietary restriction on metabolic parameters, which affectedsimilarly both adults and elderly subjects.8This work has successfully proved the potential of metabolomic approach inidentification of biomarkers of specific dairy intake. However, we also found limitations ofmetabolomics, notably identification of metabolites. Thus, more effort should be put into theimprovement of identification methodologies. Given that the association between different dataset such as dietary, biochemical, and gut microbiota data and metabolomic data brought a newinsight in biomarker discovery, integrating metabolomic datasets with other datasets such astranscriptomics, lipidomics, and gut microbiome could be an interesting approach for the futurestudies.