Gut Microbiota in Patients with Different Metabolic Statuses: Moscow Study

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Reviewed Marked as Reviewed by Shaimaa Elsafoury on 2021/02/09
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI
Authors
Kashtanova DA, Tkacheva ON, Doudinskaya EN, Strazhesko ID, Kotovskaya YV, Popenko AS, Tyakht AV, Alexeev DG
Journal
Microorganisms
Year
2018
Keywords:
cardiovascular risk factors, diet, glucose metabolism, gut microbiota, metabolic status
The aim of this paper was to study gut microbiota composition in patients with different metabolic statuses. METHODS: 92 participants aged 25⁻76 years (26 of whom were men), with confirmed absence of cardiovascular and other chronic diseases (but with the possible presence of cardiovascular risk factors) were included. Carotid ultrasound examinations, 16S rRNA sequencing of stool samples and diet assessments were performed. Statistical analysis was performed using R programming language, 3.1.0. RESULTS: Enterotyping yielded two clusters differentiated by alpha-diversity. Intima-media thickness was higher in the cluster with lower diversity (adj. p < 0.001). Obesity was associated with higher Serratia (adj. p = 0.003) and Prevotella (adj. p < 0.0003) in relative abundance. Abdominal obesity was associated with higher abundance of Serratia (adj. p = 0.004) and Prevotella (adj. p = 0.0008) and lower levels of Oscillospira (adj. p = 0.0005). Glucose metabolism disturbances were associated with higher Blautia (adj. p = 0.0007) and Serratia (adj. p = 0.003) prevalence. Arterial hypertension was associated with high Blautia levels (adj. p = 0.002). The Blautia genus strongly correlated with low resistant starch consumption (adj. p = 0.007). A combination of high-fat diet and elevated Blautia levels was very common for diabetes mellitus type 2 patients (adj. p = 0.0001). CONCLUSION: The results show that there is a relationship between metabolic changes and higher representation of opportunistic pathogens and low diversity of gut microbiota even in apparently healthy participants.

Experiment 1


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

Curated date: 2021/01/10

Curator: WikiWorks

Revision editor(s): WikiWorks

Subjects

Location of subjects
Russian Federation
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
low BMI
Group 1 name Corresponds to the case (exposed) group for case-control studies
High BMI
Group 0 sample size Number of subjects in the control (unexposed) group
69
Group 1 sample size Number of subjects in the case (exposed) group
23
Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any)
3 months

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
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
sex, age


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 2

Description: Gut microbiota in patients with obesity

Abundance in Group 1: increased abundance in High BMI

NCBI Quality ControlLinks
Serratia
Prevotella

Revision editor(s): WikiWorks

Experiment 2


Reviewed Marked as Reviewed by LGeistlinger on 2021/04/12

Curated date: 2021/01/10

Curator: WikiWorks

Revision editor(s): WikiWorks

Differences from previous experiment shown

Subjects

Group 0 name Corresponds to the control (unexposed) group for case-control studies
non-abdominal obesity
Group 1 name Corresponds to the case (exposed) group for case-control studies
Abdominal obesity
Group 0 sample size Number of subjects in the control (unexposed) group
39
Group 1 sample size Number of subjects in the case (exposed) group
53

Lab analysis

Statistical Analysis

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 2

Description: Gut microbiota in patients with obesity

Abundance in Group 1: increased abundance in Abdominal obesity

NCBI Quality ControlLinks
Serratia
Prevotella

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 2

Description: Gut microbiota in patients with obesity

Abundance in Group 1: decreased abundance in Abdominal obesity

NCBI Quality ControlLinks
Oscillospira

Revision editor(s): WikiWorks