Yoghurt consumption is associated with changes in the composition of the human gut microbiome and metabolome/Experiment 4
From BugSigDB
Needs review
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
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- High Yoghurt consumers
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- High Yoghurt consumers refers to individuals that consume yoghurt more than 5times in a week.
- Group 0 sample size Number of subjects in the control (unexposed) group
- 144
- Group 1 sample size Number of subjects in the case (exposed) group
- 217
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, Confounders controlled for: "family structure" 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.family structure
Signature 1
Needs review
Source: Fig. 1C-D
Description: Differential abundance of taxa between high yoghurt eaters and non-yoghurt eaters using linear regression.
Abundance in Group 1: increased abundance in High Yoghurt consumers
| NCBI | Quality Control | Links |
|---|---|---|
| Streptococcus thermophilus | ||
| Bifidobacterium animalis |
Revision editor(s): KateRasheed
