Association of dietary fibre intake and gut microbiota in adults

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Reviewed Marked as Reviewed by Claregrieve1 on 2022/10/4
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI
Authors
Lin D, Peters BA, Friedlander C, Freiman HJ, Goedert JJ, Sinha R, Miller G, Bernstein MA, Hayes RB, Ahn J
Journal
The British journal of nutrition
Year
2018
Keywords:
FC fold change, NCI National Cancer Institute, NYU New York University, Cross-sectional studies, Dietary fibre intake, Epidemiology, Gut microbiome
Increasing evidence indicates that gut microbiota may influence colorectal cancer risk. Diet, particularly fibre intake, may modify gut microbiota composition, which may affect cancer risk. We investigated the relationship between dietary fibre intake and gut microbiota in adults. Using 16S rRNA gene sequencing, we assessed gut microbiota in faecal samples from 151 adults in two independent study populations: National Cancer Institute (NCI), n 75, and New York University (NYU), n 76. We calculated energy-adjusted fibre intake based on FFQ. For each study population with adjustment for age, sex, race, BMI and smoking, we evaluated the relationship between fibre intake and gut microbiota community composition and taxon abundance. Total fibre intake was significantly associated with overall microbial community composition in NYU (P=0·008) but not in NCI (P=0·81). In a meta-analysis of both study populations, higher fibre intake tended to be associated with genera of class Clostridia, including higher abundance of SMB53 (fold change (FC)=1·04, P=0·04), Lachnospira (FC=1·03, P=0·05) and Faecalibacterium (FC=1·03, P=0·06), and lower abundance of Actinomyces (FC=0·95, P=0·002), Odoribacter (FC=0·95, P=0·03) and Oscillospira (FC=0·96, P=0·06). A species-level meta-analysis showed that higher fibre intake was marginally associated with greater abundance of Faecalibacterium prausnitzii (FC=1·03, P=0·07) and lower abundance of Eubacterium dolichum (FC=0·96, P=0·04) and Bacteroides uniformis (FC=0·97, P=0·05). Thus, dietary fibre intake may impact gut microbiota composition, particularly class Clostridia, and may favour putatively beneficial bacteria such as F. prausnitzii. These findings warrant further understanding of diet-microbiota relationships for future development of colorectal cancer prevention strategies.

Experiment 1


Reviewed Marked as Reviewed by Claregrieve1 on 2022/10/4

Curated date: 2021/01/10

Curator: WikiWorks

Revision editor(s): Claregrieve1, WikiWorks

Subjects

Location of subjects
United States of America
Host species Species from which microbiome was sampled (if applicable)
Homo sapiens
Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces
Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
diet Dietary,Diets,diet
Group 0 name Corresponds to the control (unexposed) group for case-control studies
high fiber (Q3 and Q4)
Group 1 name Corresponds to the case (exposed) group for case-control studies
low fiber (Q1 and Q2)
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
subjects in the lower quartiles (Q1 and Q2) of fiber intake
Group 0 sample size Number of subjects in the control (unexposed) group
75
Group 1 sample size Number of subjects in the case (exposed) group
76
Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any)
no "long term" antibiotics use

Lab analysis

Sequencing type
16S
16S variable region One or more hypervariable region(s) of the bacterial 16S gene
V3-V4
Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
Illumina

Statistical Analysis

Statistical test
DESeq2
Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
0.05
MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
Yes
Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment
age, body mass index, smoking behavior, race, sex

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness
unchanged

Signature 1

Reviewed Marked as Reviewed by Claregrieve1 on 2022/10/4

Curated date: 2021/01/10

Curator: Lora Kasselman

Revision editor(s): Claregrieve1, WikiWorks

Source: Table 2.

Description: Differential microbial abundance between lower fibre intake and higher fibre intake subjects

Abundance in Group 1: increased abundance in low fiber (Q1 and Q2)

NCBI Quality ControlLinks
Odoribacter
Bacteroides uniformis
Actinomyces
Amedibacillus dolichus CAG:375

Revision editor(s): Claregrieve1, WikiWorks

Signature 2

Reviewed Marked as Reviewed by Claregrieve1 on 2022/10/4

Curated date: 2021/01/10

Curator: Lora Kasselman

Revision editor(s): Claregrieve1, Merit, WikiWorks

Source: Table 2.

Description: Differential microbial abundance between lower fibre intake and higher fibre intake subjects

Abundance in Group 1: decreased abundance in low fiber (Q1 and Q2)

NCBI Quality ControlLinks
Odoribacter
Oscillospira
Actinomyces
Amedibacillus dolichus CAG:375
Bacteroides uniformis

Revision editor(s): Claregrieve1, Merit, WikiWorks