Gut Microbiota in Patients with Different Metabolic Statuses: Moscow Study

Study information

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

study design

cross-sectional observational, not case-control

Citation

PMID PubMed identifier for scientific articles.

30257444

DOI Digital object identifier for electronic documents.

10.3390/microorganisms6040098

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

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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 (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: obesity Adiposis,Adiposity,Obese,Obese (finding),obesity,Obesity (disorder),Obesity [Ambiguous],obesity disease,obesity disorder,Obesity NOS,Obesity, unspecified,Overweight and 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

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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 Control	Links
Serratia
Prevotella

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Experiment 2

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

Curated date: 2021/01/10

Curator: WikiWorks

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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