Evidence map›Paper›PMID 33471048›Full record

ArticleThe American journal of clinical nutrition2021

Long-term dietary intake from infancy to late adolescence is associated with gut microbiota composition in young adulthood.

Kolade Oluwagbemigun, Aoife N O'Donovan, Kirsten Berding, Katriona Lyons, Ute Alexy, Matthias Schmid, Gerard Clarke, Catherine Stanton, John Cryan, Ute Nöthlings

Open access · greenAbstract read
In one paragraph

Article in The American journal of clinical nutrition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.2field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 26 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 2 countries.

Kolade OluwagbemigunUnit of Nutritional Epidemiology, Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany.
Aoife N O'DonovanAPC Microbiome Ireland, University College Cork, Cork, Ireland.
Kirsten BerdingAPC Microbiome Ireland, University College Cork, Cork, Ireland.
Katriona LyonsAPC Microbiome Ireland, University College Cork, Cork, Ireland.
Ute AlexyUnit of Nutritional Epidemiology, Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany.
Matthias SchmidDepartment of Medical Biometry, Informatics, and Epidemiology, University Hospital Bonn, University of Bonn, Bonn, Germany.
Gerard ClarkeAPC Microbiome Ireland, University College Cork, Cork, Ireland.
Catherine StantonAPC Microbiome Ireland, University College Cork, Cork, Ireland.
John CryanAPC Microbiome Ireland, University College Cork, Cork, Ireland.
Ute NöthlingsUnit of Nutritional Epidemiology, Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany.
University of Bonn · DETeagasc - The Irish Agriculture and Food Development Authority · IEUniversity College Cork · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGut microbiota composition as influenced by long-term diet may be associated with the risk of adult chronic diseases. Thus, establishing the relation of long-term diet, particularly starting from early life, with adult microbiota composition would be an important research advance.

objectiveWe aimed to investigate the association of long-term intake of energy, carbohydrate, fiber, protein, and fat from infancy to late adolescence with microbiota composition in adulthood.

methodsWithin the prospective DOrtmund Nutritional and Anthropometric Longitudinally Designed (DONALD) Study, we sampled stool 1 or 2 times within 1 y from 128 adults (median age: 29 y). Microbiota composition was profiled by 16S ribosomal RNA sequencing. Annual dietary records from age 1 to 18 y were retrieved. We estimated trajectories of energy, energy-adjusted carbohydrate, fiber, protein, and fat intake with multilevel models, producing predicted intake at age 1 y and rates of change in intake. A multivariate, zero-inflated, logistic-normal model was used to model the association between intake trajectories and the composition of 158 genera in single-sampled individuals. Associations found in this model were confirmed in double-sampled individuals using a zero-inflated Beta regression model.

resultsAdjusting for covariates and temporal differences in microbiota composition, long-term carbohydrate intake was associated with 3 genera. Specifically, carbohydrate intake at age 1 y was negatively associated with Phascolarctobacterium [coefficient = -4.31; false discovery rate (FDR)-adjusted P = 0.006] and positively associated with Dialister (coefficient = 3.06; FDR-adjusted P = 0.003), and the rate of change in carbohydrate intake was positively associated with Desulfovibrio (coefficient = 13.16; FDR-adjusted P = 0.00039). Energy and other macronutrients were not associated with any genus.

conclusionsThis work links long-term carbohydrate intake to microbiota composition. Considering the associations of high carbohydrate intake and microbiota composition with some diseases, these findings could inform the development of gut microbiota-targeted dietary recommendations for disease prevention.

Indexed as

AgingChild Nutritional Physiological PhenomenaGastrointestinal MicrobiomeAdolescentAdultBacteriaChildChild, PreschoolDietary CarbohydratesDNA, BacterialFecesHumansInfantRNA, BacterialRNA, Ribosomal, 16SDietary CarbohydratesDNA, BacterialRNA, BacterialRNA, Ribosomal, 16S3-day weighed dietary recordscarbohydrate intakeDesulfovibrioDialisterDONALD studygut microbiota compositionlong-term dietPhascolarctobacterium

Identifiers

PMID33471048
PMCPMC7948843
OpenAlexW3124213695

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.