Pediatric obesity is associated with an altered gut microbiota and discordant shifts in Firmicutes populations

From BugSigDB
Reviewed Marked as Reviewed by Shaimaa Elsafoury on 2021/02/09
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI
Authors
Riva A, Borgo F, Lassandro C, Verduci E, Morace G, Borghi E, Berry D
Journal
Environmental microbiology
Year
2017
An altered gut microbiota has been linked to obesity in adulthood, although little is known about childhood obesity. The aim of this study was to characterize the composition of the gut microbiota in obese (n = 42) and normal-weight (n = 36) children aged 6 to 16. Using 16S rRNA gene-targeted sequencing, we evaluated taxa with differential abundance according to age- and sex-normalized body mass index (BMI z-score). Obesity was associated with an altered gut microbiota characterized by elevated levels of Firmicutes and depleted levels of Bacteroidetes. Correlation network analysis revealed that the gut microbiota of obese children also had increased correlation density and clustering of operational taxonomic units (OTUs). Members of the Bacteroidetes were generally better predictors of BMI z-score and obesity than Firmicutes, which was likely due to discordant responses of Firmicutes OTUs. In accordance with these observations, the main metabolites produced by gut bacteria, short chain fatty acids (SCFAs), were higher in obese children, suggesting elevated substrate utilisation. Multiple taxa were correlated with SCFA levels, reinforcing the tight link between the microbiota, SCFAs and obesity. Our results suggest that gut microbiota dysbiosis and elevated fermentation activity may be involved in the etiology of childhood obesity.

Experiment 1


Reviewed Marked as Reviewed by Shaimaa Elsafoury on 2021/02/09

Curated date: 2021/01/10

Curator: WikiWorks

Revision editor(s): WikiWorks, Victoria

Subjects

Location of subjects
Italy
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
Obesity Adiposis,Adiposity,Obese,Obese (finding),obesity,Obesity (disorder),Obesity [Ambiguous],obesity disease,obesity disorder,Obesity NOS,Obesity, unspecified,Overweight and obesity,Obesity
Group 0 name Corresponds to the control (unexposed) group for case-control studies
controls
Group 1 name Corresponds to the case (exposed) group for case-control studies
pediatric obese
Group 0 sample size Number of subjects in the control (unexposed) group
36
Group 1 sample size Number of subjects in the case (exposed) group
42
Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any)
6 months

Lab analysis

Sequencing type
16S
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).
raw counts
Statistical test
Linear 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, sex

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness
unchanged
Chao1 Abundance-based estimator of species richness
unchanged
Inverse Simpson Modification of Simpsons index D as 1/D to obtain high values in datasets of high diversity and vice versa
unchanged
Richness Number of species
unchanged

Signature 1

Reviewed Marked as Reviewed by Shaimaa Elsafoury on 2021/02/09

Curated date: 2021/01/10

Curator: Marianthi Thomatos

Revision editor(s): WikiWorks

Source: Table 1 & Supplementary Table 5

Description: Differential abundance in pediatric obesity versus normal weight controls

Abundance in Group 1: increased abundance in pediatric obese

NCBI Quality ControlLinks
Bacillota
Clostridia
Eubacteriales
Oscillospiraceae
Faecalibacterium prausnitzii

Revision editor(s): WikiWorks

Signature 2

Reviewed Marked as Reviewed by Shaimaa Elsafoury on 2021/02/09

Curated date: 2021/01/10

Curator: Marianthi Thomatos

Revision editor(s): WikiWorks

Source: Table 1 & Supplementary Table 5

Description: Differential abundance in pediatric obesity versus normal weight controls

Abundance in Group 1: decreased abundance in pediatric obese

NCBI Quality ControlLinks
Bacteroidota
Bacteroidia
Bacteroidales
Bacteroidaceae
Bacteroides
Phocaeicola vulgatus
Bacteroides stercoris

Revision editor(s): WikiWorks