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Enregistrement W2940758790 · doi:10.3389/fnut.2019.00058

Integrated Analysis of Human Milk Microbiota With Oligosaccharides and Fatty Acids in the CHILD Cohort

2019· article· en· W2940758790 sur OpenAlex
Shirin Moossavi, Faisal Atakora, Kozeta Miliku, Shadi Sepehri, Bianca Robertson, Qing Duan, Allan B. Becker, Piush J. Mandhane, Stuart E. Turvey, Theo J. Moraes, Diana L. Lefebvre, Malcolm R. Sears, Padmaja Subbarao, Catherine J. Field, Lars Bode, Ehsan Khafipour, Meghan B. Azad

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Notice bibliographique

RevueFrontiers in Nutrition · 2019
Typearticle
Langueen
DomaineNursing
ThématiqueInfant Nutrition and Health
Établissements canadiensSickKids FoundationUniversity of TorontoUniversity of AlbertaHospital for Sick ChildrenUniversity of British ColumbiaMcMaster UniversityQueen's UniversityChildren's Hospital Research Institute of ManitobaUniversity of Manitoba
Organismes subventionnairesCanadian Institutes of Health ResearchUniversity of AlbertaCanadian Lung AssociationMcMaster UniversityCanada Research ChairsHeart and Stroke Foundation of Canada
Mots-clésBiologyFatty acidBreast milkPrincipal component analysisDocosahexaenoic acidFood scienceNeisseriaBiochemistryBacteriaPolyunsaturated fatty acidGeneticsMathematics

Résumé

récupéré en direct d'OpenAlex

Background: Human milk contains many bioactive components that are typically studied in isolation, including bacteria. We performed an integrated analysis of human milk oligosaccharides and fatty acids to explore their associations with milk microbiota. Methods: We studied a sub-sample of 393 mothers in the CHILD birth cohort. Milk was collected at 3-4 months postpartum. Microbiota was analysed by 16S rRNA gene V4 sequencing. Oligosaccharides and fatty acids were analysed by rapid high-throughput high performance and gas liquid chromatography, respectively. Dimension reduction was performed with principal component analysis for oligosaccharides and fatty acids. Centre log-ratio transformation was applied to all three components. Associations between components were assessed using Spearman rank correlation, network visualization, multivariable linear regression, redundancy analysis, and structural equation modelling. P-values were adjusted for multiple comparisons. Key covariates were considered, including fucosyltransferase-2 (FUT2) secretor status of mother and infant, method of feeding (direct breastfeeding or pumped breast milk), and maternal fish oil supplement use. Results: Overall, correlations were strongest between milk components of the same type. For example, FUT2-dependent HMOs were positively correlated with each other, and Staphylococcus was negatively correlated with other core taxa. Some associations were also observed between components of different types. Using redundancy analysis and structural equation modelling, the overall milk fatty acid profile was significantly associated with milk microbiota composition. In addition, some individual fatty acids (22:6n3 (docosahexaenoic acid), 22:5n3, 20:5n3, 17:0, 18:0) and oligosaccharides (fucosyl-lacto-N-hexaose, lacto-N-hexaose, lacto-N-fucopentaose I) were associated with microbiota α diversity, while others (C18:0, 3’-sialyllactose, disialyl-lacto-N-tetraose) were associated with overall microbiota composition. Only a few significant associations between individual HMOs and microbiota were observed; notably, among mothers using breast pumps, Bifidobacterium prevalence was associated with lower abundances of disialyl-lacto-N-hexaose. Additionally, among non-secretor mothers, Staphylococcus was positively correlated with sialylated HMOs. Conclusion: Using multiple approaches to integrate and analyse milk microbiota, oligosaccharides, and fatty acids, we observed some associations between different milk components and microbiota, some of which were modified by secretor status and/or breastfeeding practices. Additional research is needed to further validate and mechanistically characterize these associations and determine their relevance to infant gut and respiratory microbiota development and health.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,009
Score d'incertitude au seuil0,396

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,007
Tête enseignante GPT0,242
Écart entre enseignants0,235 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle