Dietary sugar and saturated fat consumption associated with changes in the gastrointestinal microbiome during pregnancy.

Pregnancy body mass index dietary intake microbiota

Journal

The Journal of nutrition
ISSN: 1541-6100
Titre abrégé: J Nutr
Pays: United States
ID NLM: 0404243

Informations de publication

Date de publication:
20 Sep 2024
Historique:
received: 06 10 2023
revised: 29 07 2024
accepted: 10 09 2024
medline: 23 9 2024
pubmed: 23 9 2024
entrez: 22 9 2024
Statut: aheadofprint

Résumé

Growing evidence supports changes in the gastrointestinal microbiome over the course of pregnancy may have an impact on the short and long-term health of both the mother and the child. Our objective was to explore the association of diet quality, as measured by the Healthy Eating Index (HEI), with the composition and Gene Ontology (GO) representation of microbial function in the maternal gastrointestinal microbiome during pregnancy. We conducted a retrospective, observational analysis of n=185 pregnant participants in the Pregnancy Eating Attributes Study (PEAS) study. Maternal dietary intake was assessed in the first trimester using the Automated Self-Administered 24-Hour Recall (ASA24) method, from which the Healthy Eating Index 2015 was calculated. Rectal swabs were obtained in the second trimester and sequenced using the NovaSeq 6000 system shotgun platform. We used unsupervised clustering to identify microbial enterotypes representative of maternal taxa and GO functional term composition. Multivariable linear models were used to identify associations between taxa, functional terms, and food components while controlling for relevant covariates. Multinomial regression was then used to predict enterotype membership based on a participant's HEI food component score. Those in the high diet quality tertile had a lower early pregnancy BMI (mean [M]=23.48 kg/m2, SD=3.38) compared to the middle (M=27.35, SD=6.01) and low (M=27.49, SD=6.99) diet quality tertiles (p<0.01). There were no statistically significant associations between the HEI components or the total HEI score and the four alpha diversity measures. Differences in taxa and GO term enterotypes were found in participants with, but not limited to, a higher saturated fat component score (β=1.35, p=0.01), added sugar HEI component (β=0.07, p<0.001), and higher total dairy score (β=1.58, p=0.01). Specific dietary components are associated with microbial composition and function in the second trimester of pregnancy. These findings provide a foundation for future testable hypotheses.

Sections du résumé

BACKGROUND BACKGROUND
Growing evidence supports changes in the gastrointestinal microbiome over the course of pregnancy may have an impact on the short and long-term health of both the mother and the child.
OBJECTIVE OBJECTIVE
Our objective was to explore the association of diet quality, as measured by the Healthy Eating Index (HEI), with the composition and Gene Ontology (GO) representation of microbial function in the maternal gastrointestinal microbiome during pregnancy.
METHODS METHODS
We conducted a retrospective, observational analysis of n=185 pregnant participants in the Pregnancy Eating Attributes Study (PEAS) study. Maternal dietary intake was assessed in the first trimester using the Automated Self-Administered 24-Hour Recall (ASA24) method, from which the Healthy Eating Index 2015 was calculated. Rectal swabs were obtained in the second trimester and sequenced using the NovaSeq 6000 system shotgun platform. We used unsupervised clustering to identify microbial enterotypes representative of maternal taxa and GO functional term composition. Multivariable linear models were used to identify associations between taxa, functional terms, and food components while controlling for relevant covariates. Multinomial regression was then used to predict enterotype membership based on a participant's HEI food component score.
RESULTS RESULTS
Those in the high diet quality tertile had a lower early pregnancy BMI (mean [M]=23.48 kg/m2, SD=3.38) compared to the middle (M=27.35, SD=6.01) and low (M=27.49, SD=6.99) diet quality tertiles (p<0.01). There were no statistically significant associations between the HEI components or the total HEI score and the four alpha diversity measures. Differences in taxa and GO term enterotypes were found in participants with, but not limited to, a higher saturated fat component score (β=1.35, p=0.01), added sugar HEI component (β=0.07, p<0.001), and higher total dairy score (β=1.58, p=0.01).
CONCLUSIONS CONCLUSIONS
Specific dietary components are associated with microbial composition and function in the second trimester of pregnancy. These findings provide a foundation for future testable hypotheses.

Identifiants

pubmed: 39307280
pii: S0022-3166(24)01033-2
doi: 10.1016/j.tjnut.2024.09.016
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.

Déclaration de conflit d'intérêts

Declaration of Competing Interest Anna Maria Siega-RizThe authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Siega-Riz reports financial support was provided by National Institute of Child Health and Human Development. Siega-Riz, AM reports a relationship with International Food Information Council that includes: board membership and travel reimbursement. Caitlin DreisbachThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Shyamal PeddadaThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Tonja NanselThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Wanda NicholsonThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Caitlin Dreisbach (C)

School of Nursing, University of Rochester, Rochester, NY, USA; Goregen Institute for Data Science, University of Rochester, Rochester, NY, USA. Electronic address: Caitlin_dreisbach@urmc.rochester.edu.

Tonja Nansel (T)

Social and Behavioral Sciences Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, USA.

Shyamal Peddada (S)

Biostatistics & Computational Biology Branch, National Institute for Environmental Health Sciences, Bethesda, MD, USA.

Wanda Nicholson (W)

Milken Institute School of Public Health, George Washington University, Washington, D.C., USA.

Anna Maria Siega-Riz (AM)

School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA.

Classifications MeSH