MétaCan
Menu
Back to cohort
Record W2908338457 · doi:10.1186/s40168-018-0608-z

Impact of early events and lifestyle on the gut microbiota and metabolic phenotypes in young school-age children

2019· article· en· W2908338457 on OpenAlexfundno aff
Huanzi Zhong, John Penders, Zhun Shi, Huahui Ren, Kaiye Cai, Chao Fang, Qiuxia Ding, Carel Thijs, Ellen E. Blaak, Coen D.A. Stehouwer, Xun Xu, Huanming Yang, Jian Wang, Jun Wang, Daisy Jonkers, Ad Masclee, Susanne Brix, Junhua Li, Ilja C.W. Arts, Karsten Kristiansen

Bibliographic record

VenueMicrobiome · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
FundersStichting Astma BestrijdingUniversity of TorontoGovernment of Jiangxi ProvinceChinese Diabetes SocietyZonMwJoint Programming Initiative A healthy diet for a healthy lifeEuropean Foundation for the Study of DiabetesEli Lilly and Company
KeywordsBiologyPhenotypeGut floraMedical microbiologyMicrobial ecologyGeneticsImmunologyBacteriaGene

Abstract

fetched live from OpenAlex

BACKGROUND: The gut microbiota evolves from birth and is in early life influenced by events such as birth mode, type of infant feeding, and maternal and infant antibiotics use. However, we still have a gap in our understanding of gut microbiota development in older children, and to what extent early events and pre-school lifestyle modulate the composition of the gut microbiota, and how this impinges on whole body metabolic regulation in school-age children. RESULTS: Taking advantage of the KOALA Birth Cohort Study, a long-term prospective birth cohort in the Netherlands with extensive collection of high-quality host metadata, we applied shotgun metagenomics sequencing and systematically investigated the gut microbiota of children at 6-9 years of age. We demonstrated an overall adult-like gut microbiota in the 281 Dutch school-age children and identified 3 enterotypes dominated by the genera Bacteroides, Prevotella, and Bifidobacterium, respectively. Importantly, we found that breastfeeding duration in early life and pre-school dietary lifestyle correlated with the composition and functional competences of the gut microbiota in the children at school age. The correlations between pre-school dietary lifestyle and metabolic phenotypes exhibited a striking enterotype dependency. Thus, an inverse correlation between high dietary fiber consumption and low plasma insulin levels was only observed in individuals with the Bacteroides and Prevotella enterotypes, but not in Bifidobacterium enterotype individuals in whom the gut microbiota displayed overall lower microbial gene richness, alpha-diversity, functional potential for complex carbohydrate fermentation, and butyrate and succinate production. High total fat consumption and elevated plasma free fatty acid levels in the Bifidobacterium enterotype are associated with the co-occurrence of Streptococcus. CONCLUSIONS: Our work highlights the persistent effects of breastfeeding duration and pre-school dietary lifestyle in affecting the gut microbiota in school-age children and reveals distinct compositional and functional potential in children according to enterotypes. The findings underscore enterotype-specific links between the host metabolic phenotypes and dietary patterns, emphasizing the importance of microbiome-based stratification when investigating metabolic responses to diets. Future diet intervention studies are clearly warranted to examine gut microbe-diet-host relationships to promote knowledge-based recommendations in relation to improving metabolic health in children.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.243
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations222
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueMicrobiomeSame topicGut microbiota and healthFrench-language works237,207