Yoghurt consumption is associated with changes in the composition of the human gut microbiome and metabolome/Experiment 6

From BugSigDB


Needs review

Curated date: 2024/11/14

Curator: KateRasheed

Revision editor(s): KateRasheed

Subjects

Location of subjects
United Kingdom
Host species Species from which microbiome was sampled. Contact us to have more species added.
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,feces
Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
Beverage consumption measurement Beverage consumption measurement,beverage consumption measurement
Group 0 name Corresponds to the control (unexposed) group for case-control studies
Non-Yoghurt consumers(didn't consume yoghurt 24hrs before sampling)
Group 1 name Corresponds to the case (exposed) group for case-control studies
High Yoghurt consumers(consumed yoghurt 24hrs before sampling)
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
High Yoghurt consumers(consumed yoghurt 24hrs before sampling) refers to those who ate yoghurt a day before sampling (24hours before sampling).
Group 0 sample size Number of subjects in the control (unexposed) group
43
Group 1 sample size Number of subjects in the case (exposed) group
27

Lab analysis

Sequencing type
WMS
16S variable region One or more hypervariable region(s) of the bacterial 16S gene
Not specified
Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
Illumina

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
relative abundances
Statistical test
Mixed-Effects Regression
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, sex, Confounders controlled for: "healthy eating index" is not in the list (abnormal glucose tolerance, acetaldehyde, acute graft vs. host disease, acute lymphoblastic leukemia, acute myeloid leukemia, adenoma, age, AIDS, alcohol consumption measurement, alcohol drinking, ...) of allowed values.healthy eating index


Signature 1

Needs review

Curated date: 2024/11/15

Curator: KateRasheed

Revision editor(s): KateRasheed

Source: Fig. 2A-B

Description: Differential abundant taxa between non-yoghurt consumers (didn't consume yoghurt 24hrs before sampling) and high yoghurt eaters(consumed yoghurt 24hrs before sampling).

Abundance in Group 1: increased abundance in High Yoghurt consumers(consumed yoghurt 24hrs before sampling)

NCBI Quality ControlLinks
Bifidobacterium animalis subsp. lactis
Streptococcus thermophilus

Revision editor(s): KateRasheed