Cargando…

A posteriori dietary patterns better explain variations of the gut microbiome than individual markers in the American Gut Project

BACKGROUND: Individual diet components and specific dietary regimens have been shown to impact the gut microbiome. OBJECTIVES: Here, we explored the contribution of long-term diet by searching for dietary patterns that would best associate with the gut microbiome in a population-based cohort. METHOD...

Descripción completa

Detalles Bibliográficos
Autores principales: Cotillard, Aurélie, Cartier-Meheust, Agnès, Litwin, Nicole S, Chaumont, Soline, Saccareau, Mathilde, Lejzerowicz, Franck, Tap, Julien, Koutnikova, Hana, Lopez, Diana Gutierrez, McDonald, Daniel, Song, Se Jin, Knight, Rob, Derrien, Muriel, Veiga, Patrick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8827078/
https://www.ncbi.nlm.nih.gov/pubmed/34617562
http://dx.doi.org/10.1093/ajcn/nqab332
_version_ 1784647556388618240
author Cotillard, Aurélie
Cartier-Meheust, Agnès
Litwin, Nicole S
Chaumont, Soline
Saccareau, Mathilde
Lejzerowicz, Franck
Tap, Julien
Koutnikova, Hana
Lopez, Diana Gutierrez
McDonald, Daniel
Song, Se Jin
Knight, Rob
Derrien, Muriel
Veiga, Patrick
author_facet Cotillard, Aurélie
Cartier-Meheust, Agnès
Litwin, Nicole S
Chaumont, Soline
Saccareau, Mathilde
Lejzerowicz, Franck
Tap, Julien
Koutnikova, Hana
Lopez, Diana Gutierrez
McDonald, Daniel
Song, Se Jin
Knight, Rob
Derrien, Muriel
Veiga, Patrick
author_sort Cotillard, Aurélie
collection PubMed
description BACKGROUND: Individual diet components and specific dietary regimens have been shown to impact the gut microbiome. OBJECTIVES: Here, we explored the contribution of long-term diet by searching for dietary patterns that would best associate with the gut microbiome in a population-based cohort. METHODS: Using a priori and a posteriori approaches, we constructed dietary patterns from an FFQ completed by 1800 adults in the American Gut Project. Dietary patterns were defined as groups of participants or combinations of food variables (factors) driven by criteria ranging from individual nutrients to overall diet. We associated these patterns with 16S ribosomal RNA–based gut microbiome data for a subset of 744 participants. RESULTS: Compared to individual features (e.g., fiber and protein), or to factors representing a reduced number of dietary features, 5 a posteriori dietary patterns based on food groups were best associated with gut microbiome beta diversity (P ≤ 0.0002). Two patterns followed Prudent-like diets—Plant-Based and Flexitarian—and exhibited the highest Healthy Eating Index 2010 (HEI-2010) scores. Two other patterns presented Western-like diets with a gradient in HEI-2010 scores. A fifth pattern consisted mostly of participants following an Exclusion diet (e.g., low carbohydrate). Notably, gut microbiome alpha diversity was significantly lower in the most Western pattern compared to the Flexitarian pattern (P ≤ 0.009), and the Exclusion diet pattern was associated with low relative abundance of Bifidobacterium (P ≤ 1.2 × 10(–7)), which was better explained by diet than health status. CONCLUSIONS: We demonstrated that global-diet a posteriori patterns were more associated with gut microbiome variations than individual dietary features among adults in the United States. These results confirm that evaluating diet as a whole is important when studying the gut microbiome. It will also facilitate the design of more personalized dietary strategies in general populations.
format Online
Article
Text
id pubmed-8827078
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-88270782022-02-10 A posteriori dietary patterns better explain variations of the gut microbiome than individual markers in the American Gut Project Cotillard, Aurélie Cartier-Meheust, Agnès Litwin, Nicole S Chaumont, Soline Saccareau, Mathilde Lejzerowicz, Franck Tap, Julien Koutnikova, Hana Lopez, Diana Gutierrez McDonald, Daniel Song, Se Jin Knight, Rob Derrien, Muriel Veiga, Patrick Am J Clin Nutr Original Research Communications BACKGROUND: Individual diet components and specific dietary regimens have been shown to impact the gut microbiome. OBJECTIVES: Here, we explored the contribution of long-term diet by searching for dietary patterns that would best associate with the gut microbiome in a population-based cohort. METHODS: Using a priori and a posteriori approaches, we constructed dietary patterns from an FFQ completed by 1800 adults in the American Gut Project. Dietary patterns were defined as groups of participants or combinations of food variables (factors) driven by criteria ranging from individual nutrients to overall diet. We associated these patterns with 16S ribosomal RNA–based gut microbiome data for a subset of 744 participants. RESULTS: Compared to individual features (e.g., fiber and protein), or to factors representing a reduced number of dietary features, 5 a posteriori dietary patterns based on food groups were best associated with gut microbiome beta diversity (P ≤ 0.0002). Two patterns followed Prudent-like diets—Plant-Based and Flexitarian—and exhibited the highest Healthy Eating Index 2010 (HEI-2010) scores. Two other patterns presented Western-like diets with a gradient in HEI-2010 scores. A fifth pattern consisted mostly of participants following an Exclusion diet (e.g., low carbohydrate). Notably, gut microbiome alpha diversity was significantly lower in the most Western pattern compared to the Flexitarian pattern (P ≤ 0.009), and the Exclusion diet pattern was associated with low relative abundance of Bifidobacterium (P ≤ 1.2 × 10(–7)), which was better explained by diet than health status. CONCLUSIONS: We demonstrated that global-diet a posteriori patterns were more associated with gut microbiome variations than individual dietary features among adults in the United States. These results confirm that evaluating diet as a whole is important when studying the gut microbiome. It will also facilitate the design of more personalized dietary strategies in general populations. Oxford University Press 2021-10-07 /pmc/articles/PMC8827078/ /pubmed/34617562 http://dx.doi.org/10.1093/ajcn/nqab332 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Research Communications
Cotillard, Aurélie
Cartier-Meheust, Agnès
Litwin, Nicole S
Chaumont, Soline
Saccareau, Mathilde
Lejzerowicz, Franck
Tap, Julien
Koutnikova, Hana
Lopez, Diana Gutierrez
McDonald, Daniel
Song, Se Jin
Knight, Rob
Derrien, Muriel
Veiga, Patrick
A posteriori dietary patterns better explain variations of the gut microbiome than individual markers in the American Gut Project
title A posteriori dietary patterns better explain variations of the gut microbiome than individual markers in the American Gut Project
title_full A posteriori dietary patterns better explain variations of the gut microbiome than individual markers in the American Gut Project
title_fullStr A posteriori dietary patterns better explain variations of the gut microbiome than individual markers in the American Gut Project
title_full_unstemmed A posteriori dietary patterns better explain variations of the gut microbiome than individual markers in the American Gut Project
title_short A posteriori dietary patterns better explain variations of the gut microbiome than individual markers in the American Gut Project
title_sort posteriori dietary patterns better explain variations of the gut microbiome than individual markers in the american gut project
topic Original Research Communications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8827078/
https://www.ncbi.nlm.nih.gov/pubmed/34617562
http://dx.doi.org/10.1093/ajcn/nqab332
work_keys_str_mv AT cotillardaurelie aposterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT cartiermeheustagnes aposterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT litwinnicoles aposterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT chaumontsoline aposterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT saccareaumathilde aposterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT lejzerowiczfranck aposterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT tapjulien aposterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT koutnikovahana aposterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT lopezdianagutierrez aposterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT mcdonalddaniel aposterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT songsejin aposterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT knightrob aposterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT derrienmuriel aposterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT veigapatrick aposterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT cotillardaurelie posterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT cartiermeheustagnes posterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT litwinnicoles posterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT chaumontsoline posterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT saccareaumathilde posterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT lejzerowiczfranck posterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT tapjulien posterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT koutnikovahana posterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT lopezdianagutierrez posterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT mcdonalddaniel posterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT songsejin posterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT knightrob posterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT derrienmuriel posterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject
AT veigapatrick posterioridietarypatternsbetterexplainvariationsofthegutmicrobiomethanindividualmarkersintheamericangutproject